U.S. patent application number 16/394018 was filed with the patent office on 2019-08-22 for systems and methods for determining measurement data of an item.
The applicant listed for this patent is Walmart Apollo, LLC. Invention is credited to Christopher Joseph Hendrick.
Application Number | 20190259048 16/394018 |
Document ID | / |
Family ID | 57882486 |
Filed Date | 2019-08-22 |
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United States Patent
Application |
20190259048 |
Kind Code |
A1 |
Hendrick; Christopher
Joseph |
August 22, 2019 |
SYSTEMS AND METHODS FOR DETERMINING MEASUREMENT DATA OF AN ITEM
Abstract
Provided are a system and method for determining a weight of an
item for purchase, comprising determining from a digital image of
an item generated by a single camera, a volume of the item, the
single camera separated from the item at a distance in a horizontal
and vertical direction established by a stationary rigid fixture;
identifying the item; accessing a database to determine an average
weight per volume measurement unit of the identified item; and
calculating a weight of the item from the volume and the average
weight per volume measurement unit.
Inventors: |
Hendrick; Christopher Joseph;
(Rogers, AR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Walmart Apollo, LLC |
Bentonville |
AR |
US |
|
|
Family ID: |
57882486 |
Appl. No.: |
16/394018 |
Filed: |
April 25, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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15204206 |
Jul 7, 2016 |
10318976 |
|
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16394018 |
|
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|
|
62197657 |
Jul 28, 2015 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01G 17/00 20130101;
A47F 9/048 20130101; G07G 1/0063 20130101; G06Q 20/208 20130101;
G07G 1/00 20130101; G06Q 30/0207 20130101 |
International
Class: |
G06Q 30/02 20060101
G06Q030/02; G06Q 20/20 20060101 G06Q020/20; G07G 1/00 20060101
G07G001/00; A47F 9/04 20060101 A47F009/04 |
Claims
1. A system for determining a weight of an item for purchase,
comprising: a single camera that generates a digital image of the
item; at least two mirrors for determining an average volume of the
item; an optical recognition device that identifies the item; a
memory that stores an average weight per volume measurement unit of
the identified item; and a special-purpose processor that
calculates an estimated weight of the item from the approximate
volume and the average weight per volume measurement unit.
2. The system of claim 1, wherein the at least two mirrors are
arranged to provide a front view, a right view, and a left view of
the image.
3. The system of claim 1, further comprising a volume calculator
that determines an area of the item from each of the front view,
the right view, and the left view of the image, and determines an
average of the three areas.
4. The system of claim 3, wherein the volume calculator determines
an average depth of the image for determining the volume.
5. The system of claim 3, further comprising an optical recognition
device that identifies the produce item, and wherein the weight of
the produce item is determined from a result of the optical
recognition device and the volume.
6. A method for determining a volume and weight of a produce item,
comprising: extrapolating a length, width, and depth of a produce
item from a two-dimensional image of the produce item; determining
a volume from a combination of the length, width, and depth of the
produce item; and determining a weight of the item from the volume.
Description
RELATED APPLICATIONS
[0001] This application is a divisional application of U.S. patent
application Ser. No. 15/204,206 filed on Jul. 7, 2016 entitled
"Methods for Determining Measurement Data of an Item," which claims
priority to U.S. Provisional Patent Application Ser. No.
62/197,657, filed on Jul. 28, 2015 entitled "Systems and Methods
for Determining Measurement Data of an Item," the entirety of each
of which is incorporated by reference herein.
FIELD
[0002] The present concepts relate generally to the measurement of
items for sale, and more specifically, to a system and method for
determining a volume and weight of a three-dimensional item from an
image of the item.
BACKGROUND
[0003] Mobile electronic devices such as smartphones are
increasingly being used in a store shopping experience. For
example, modern smartphones can store shopping lists, provide
electronic coupons that can be scanned at the phone display, and
displays advertisements when the shopper is near a store item.
BRIEF SUMMARY
[0004] In one aspect, a method for determining a weight of an item
for purchase, comprises determining from a digital image of an item
generated by a single camera a volume of the item, the single
camera separated from the item at a distance in a horizontal and
vertical direction established by a stationary rigid fixture;
identifying the item; accessing a database to determine an average
weight per volume measurement unit of the identified item; and
calculating a weight of the item from the volume and the average
weight per volume measurement unit.
[0005] In some embodiments, the item is a store produce item having
an irregular shape.
[0006] In some embodiments, determining the volume of the item
comprises: determining an average area of the item; determining an
average depth of the item; and determining an average volume by
multiplying the average area by the average depth.
[0007] In some embodiments, the volume is approximated within two
standard deviations using three different sub calculations.
[0008] In some embodiments, determining the average area includes
employing at least two mirrors to calculate multiple areas of the
item.
[0009] In some embodiments, the multiple areas of the item include:
a first area of a front view of the image; a second area of a right
reflective view of the image; and a third area of a left reflective
view of the image.
[0010] In some embodiments, the average depth is determined from an
average of pixel widths of the front view, right respective view,
and left reflective view.
[0011] In some embodiments, the height is determined by multiplying
an apparent height and a factor of a distance of the item from the
camera and a pitch of the camera to the item.
[0012] In some embodiments, determining a height of the item
includes determining a resolution of the camera, and determining a
correction ratio of pixel to millimeters.
[0013] In some embodiments, determining the volume further
comprises calculating a distance from the camera to the item by
locking a focal length of the camera to a particular distance to
provide a constant distance for applications for the basis of all
other calculations.
[0014] In some embodiments, the item is identified systematically,
optically, or manually.
[0015] In some embodiments, the method further comprises
positioning the item on an apparatus having a base and a fixture;
positioning the camera on the fixture a predetermined distance from
the item; and generating the digital image of the item.
[0016] In another aspect, a system for determining a weight of an
item for purchase, comprises a single camera that generates a
digital image of the item; at least two mirrors for determining an
average volume of the item; an optical recognition device that
identifies the item; a memory that stores an average weight per
volume measurement unit of the identified item; and a
special-purpose processor that calculates an estimated weight of
the item from the approximate volume and the average weight per
volume measurement unit.
[0017] In some embodiments, the at least two mirrors are arranged
to provide a front view, a right view, and a left view of the
image.
[0018] In some embodiments, the system further comprises a volume
calculator that determines an area of the item from each of the
front view, the right view, and the left view of the image, and
determines an average of the three areas.
[0019] In some embodiments, the volume calculator determines an
average depth of the image for determining the volume.
[0020] In some embodiments, the system further comprises an optical
recognition device that identifies the produce item, and wherein
the weight of the produce item is determined from a result of the
optical recognition device and the volume.
[0021] In another aspect, a method for determining a volume and
weight of a produce item, comprises extrapolating a length, width,
and depth of a produce item from a two-dimensional image of the
produce item; determining a volume from a combination of the
length, width, and depth of the produce item; and determining a
weight of the item from the volume.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0022] The above and further advantages of this invention may be
better understood by referring to the following description in
conjunction with the accompanying drawings, in which like numerals
indicate like structural elements and features in various figures.
The drawings are not necessarily to scale, emphasis instead being
placed upon illustrating the principles of the invention.
[0023] FIG. 1 is an illustrative side view of a system for
measuring an item, in accordance with some embodiments.
[0024] FIG. 2 is a block diagram of elements of the system of FIG.
1, in accordance with some embodiments.
[0025] FIG. 3 is flow diagram of a method for determining
measurement data of an item, in accordance with some
embodiments.
[0026] FIGS. 4A-4C are illustrative views of the system of FIG. 1
where an image of an item is captured at different vantage points
for determining multiple areas of the item, in accordance with some
embodiments.
[0027] FIGS. 5A-5C are front, left, and right views of the item
shown in FIGS. 4A-4C, in accordance with some embodiments.
DETAILED DESCRIPTION
[0028] In the following description, specific details are set forth
although it should be appreciated by one of ordinary skill in the
art that the systems and methods can be practiced without at least
some of the details. In some instances, known features or processes
are not described in detail so as to not obscure the present
invention.
[0029] Embodiments of the present concepts relate to the use of an
electronic device such as a smartphone for determining a volume,
weight, or other measurement of an item, for example, a produce
item such as a bundle of bananas, or other store items that require
such measurement data in order to determine a value of the item.
The user's electronic device can be used to determine a volume and
weight of a three-dimensional store item from an image of the item.
More specifically, systems and methods are provided that determine
a volume by extrapolating the length, width, and depth of irregular
shaped items from a 2 dimensional image. Conventional approaches
require a scale or other physical device for determining the weight
of such items. Conventional scanning applications on smartphones or
the like are not currently practical with certain store items such
as produce items which must first be weighed to determine a sale
price of the item.
[0030] A typical application may include a store customer
downloading an application onto a smartphone or other mobile
electronic device having a camera, placing a store item of interest
on an apparatus having a base and a fixture, placing the smartphone
on the fixture a predetermined distance from the item, taking a
picture of the item from the camera on the smartphone, and
receiving a display of an appropriate weight and cost of the
item.
[0031] FIG. 1 is an illustrative side view of a system 100 for
measuring an item, in accordance with some embodiments.
[0032] The system 100 includes a mobile electronic device 102, a
mirror set 104, and a processor 106, which permit a user to take a
digital image, i.e., picture, of an item 12 or object, and
calculate from the digital image the weight of the item 12.
Although a mobile electronic device is referred to herein, other
electronic devices may equally apply that are not necessarily
mobile, but may be stationary. Also, although mirrors are referred
to herein, alternative devices may equally apply such as video
screens or other elements that can capture or provide different
views of items of interest.
[0033] As shown in FIG. 2, the mobile electronic device 102
includes a camera 202 or related sensor for detecting the item 12
and encoding digital images of the item 12. The camera 202 can be
digital camera, camera phone, tablet, electronic notebook, laptop
computer, or other related device having a camera or related charge
coupled device (CCD) or complementary metal oxide semiconductor
(CMOS) device for collecting emitted light related to the item
12.
[0034] The system 100 can include a fixture 108 that attaches to
the camera 202, or as shown in FIG. 1, to the mobile electronic
device 102 housing the camera 202. The fixture 108 can extend from
a base 110, or from a stationary object such as a tabletop or floor
on which the item of interest 12, for example, a bunch of bananas,
is positioned and one or more digital images taken by the camera
202. The mirror set 104 can be positioned on the base 110 or other
stationary object at a predetermined distance from the fixture 108
and camera 202, which permits the item of interest 12, for example,
shown in FIG. 4 as a produce item, to be positioned in the field of
view of the camera 202 so that a single image can be taken of the
item 12 for determining its volume. The item 12 of interest may be
positioned between the reflective surface of the mirror set 104 and
the camera 202. A single image is taken by the camera 202 that may
capture multiple angles by way of the mirrors 104. For example, by
arranging the mirror set 104 about a periphery of the item 12, the
sides and back of the item 12 may be visible in a single image
taken by a camera facing a front of the item 12. As shown in FIGS.
4A-4C and 5A-5C, the three sides are shown illustrating that three
different views may be provided, e.g., front, left, and right views
respectively, which may be used for performing volume calculations
according to some embodiments.
[0035] The processor 106 determines an estimated weight of a
produce item based on its volume, which in turn is determined by
estimating surface areas of the produce item 12 from images taken
by the mobile electronic device 102.
[0036] To achieve this, the processor 106 may execute an
application stored in memory (not shown) that determines the
resolution capability of the camera 202, for example, by
communicating with the firmware of the device it is loaded on. The
processor 106 can determine with the given pixel density and the
known distance from the item 12 a size, for example, how many
millimeters, each pixel represents. The processor 106 may then
measure the number of pixels in each view of the item (e.g., front,
right, and left views shown in FIGS. 4A-4C and 5A-5C) and calculate
the area in pixels for that view, e.g., areas a1, a2, and a3 shown
in FIGS. 4A-4C, 5A-5C respectively. The processor 106 may then
multiply the number of pixels by the calculated amount of pixels
per millimeter to determine the number of square millimeters the
pixels represent. The foregoing steps may be performed for each
view, for example, shown in FIGS. 4A-4C, then sum those areas
together and divide by number of areas, e.g., (a1+a2+a3 )/3, to
determine the average area for the item 12.
[0037] The processor 106 may then count the number of pixels along
the average horizontal axis of the three sides and use that number
as the depth of the item and then multiply the depth by the average
area to determine the volume, for example, in cubic millimeters.
The processor 106 may then access a database of known weights per
cubic millimeter for a set of items, select the item 12 from the
stored item data, and multiply known weight value by the calculated
volume to determine an estimated weight of the item 12 shown in the
image. In some embodiments, the processor 106 may multiply the
weight of the item 12 by the retail price per pound of the item 12
to determine the total cost of the item 12.
[0038] FIG. 2 is a block diagram of elements of the system of FIG.
1, in accordance with some embodiments.
[0039] In addition to a camera 202, the mobile electronic device
102 can include optical recognition technology 204 and a memory
206. Some or all of these elements may be at the mobile electronic
device 102. In other embodiments, some of these elements may be
located externally from the mobile electronic device 102 and
communicate with each other and/or other elements of the system via
a network or other communication path, for example, wired or
wireless signals. The optical recognition technology 204 is
constructed to instantly recognize objects such as the item 12. The
mobile electronic device 102 can include a processor (not shown)
and memory 206. Stored in the memory 206 can include one or more
applications 208 executable by the device processor. One
application 208 may include recognition software that works with
the camera 202 and/or optical recognition technology 204 or related
device for identifying the item 12. Alternatively, a standalone
optical recognition device may be provided, which is physically
separate from the mobile electronic device 102.
[0040] Data related to the identified item 12 may be compared to
contents of a database 220 to determine the identity of the item
12, and other information such as the item's weight per square
millimeter. An accurate value can be generated, for example, by a
computer processor, in response to using optical recognition to
identify the item 12. The accuracy value may be used for any number
of purposes, for example, compared to a threshold value to
establish a degree of confidence that the item 12 is correctly
identified. A product code such as a PLU number may be provided to
identify the item when the accuracy value is greater than a
predetermined threshold. The identification of the item 12 could be
obtained through optical recognition, a manually input number such
as a PLU, a scanned barcode, QR code, RFID, or any unique
identifier for the item 12. Alternatively, or in addition, the item
12 can be identified systematically, optically, or manually.
[0041] The processor 106 can include a volume calculator 212, a
weight calculator 214, and a database interface 216. Some or all of
these elements may be physically collocated at the processor 106,
for example, stored at a common memory and executed by a hardware
processor. In other embodiments, at least some of these elements
may be located externally from the processor 106, for example,
located at the mobile device 102 or standalone computer, and
communicate with each other and/or other elements of the system via
a network or other communication path, for example, wired or
wireless signals.
[0042] The volume calculator 212 calculates an approximate volume
of the item 12 from a depth, width, and height of the item 12. The
volume is calculated based on pixel density instead of length, for
example, millimeters or inches. The volume can be approximated
within two standard deviations. The volume is determined by
calculating the average width or depth of the item 12 being
photographed, and multiplying it by the average area of the item
12. To account for irregular shapes, such as the bananas shown in
FIG. 1, the areas of multiple sides of the bananas may be
determined using the mirror set 104 to compensate for differences
at each vantage point.
[0043] The weight calculator 214 determines an approximate weight
of the item 12 from the calculated volume and average weight per
volume, for example, weight per cubic millimeter determined from
results retrieved from the database 220, using the results
generated by the optical recognition device 204. The database
interface 216 establishes a communication between the database 220
and the weight calculator 214.
[0044] FIG. 3 is flow diagram of a method for determining
measurement data of an item, in accordance with some
embodiments.
[0045] At block 302, the camera 202 generates a digitized image of
the item 12, which can be stored at a memory on the mobile
electronic device 102 or at a remote location. The three views are
essential for measuring irregular shapes. By determining an average
area, it compensates for the extremes that may be encountered on
objects that may have both convex and concave features.
[0046] At block 304, a volume of the item 12 is determined from the
digital image generated at block 302, for example, by multiplying
the average area by the depth of the item. Due to differing
capabilities of camera resolution, the volume can be determined
based on pixel density or related measurement, for example, by the
processor 106 described in FIG. 1. In doing so, the distance
between the camera 202 and the item 12 may be calculated. This can
be accomplished by locking the camera focal length to a specific
distance, namely, a distance to the item 12. For example, the focal
length can be locked to 1 meter, whereby the camera 202 can only
have items in the field of view that are 1 meter away in focus. The
establishing, or locking, the focal length of the camera 202 to a
specific distance, the camera 202 can capture images of the item 12
at a predetermined distance. By setting the focal length the
application will always have that distance as a known constant so
it can calculation all the other measurements as a factorial of its
distance from the item 12. The fixture 108 separated by the mirror
set 104 at a predetermined distance also allows a distance of the
camera 202 at the fixture 108 from the item 12 positioned between
the fixture 18 and the mirror 104 to be determined, so that the
camera is sufficiently focused. the fixture 18 and camera mount are
specific distances so despite what device is being used or camera
resolution, the application will always know exactly how far away
the item 12 is that is being measured.
[0047] Also, in determining volume, the height of the item 12 may
be determined. The volume calculator 212 or a phone application 208
can determine the resolution or related feature of the camera 202
when taking a picture of the item 12. This information may be
determined from bios information stored at the camera 202. Once the
volume calculator 212 receives data regarding camera resolution
and/or the related camera-related information, the volume
calculator 212 can determine a correction ratio of pixels to square
millimeters for determining an area of each view. To achieve this,
the fixture 108 can be used that holds the camera 202 at a correct
angle and distance from the item to allow a constant, for example,
the distance between the camera and item being photographed as well
as the angle the picture is being captured (to ensure an acceptable
view of both mirror reflections is provided, to be factored into
the calculation of the item volume. A height may be determined by
multiplying an apparent height and a factor of a distance of the
item from the camera and a pitch of the camera to the item.
[0048] For example, the distance between the camera 202 on the
fixture 208 and the item 12 can be determined to be lm. Also, the
camera 202 may be determined to be a 10 megapixel camera, and has a
field of view at 1 m is 2.5 m high.times.1 m wide. Here, each pixel
can be calculated to represent 0.25 square millimeters (sq. mm.)
(for example, using well-known calculations (Eq. (1)) of 25 million
sq. mm/10 million pixels).
h = a d Eq . ( 1 ) ##EQU00001##
where h is the apparent height, d is the distance of the object,
and a is the actual size of the object. To determine a "true"
height of an object in the distance, the apparent height may be
multiplied by the distance the object is from the camera 202.
Apparent height is the observable relative height of an item at
various distances. The apparent height appears to be smaller the
further away it is. The true height on the other hand is the actual
physical height of an item and is not relative to how far away it
is.
[0049] To account for odd or irregular shapes for produce items or
other items of interest of which an image is taken by the camera
202, the area of at least three sides or other surfaces are
determined to compensate for differences of each vantage point. The
two mirrors 104A, 104B of the mirror set 104 are arranged to
provide additional views of the item 12 to the camera 202, and
allows the volume calculator 212 to calculate the visible area of
the other views provided by reflected images of the other views.
The angle of the captured image allows for the camera 202 to see
the whole front of the item 12, and both reflections in both
mirrors 104.
[0050] For example, as shown in FIGS. 4A-4C, the vantage points may
include (1) a front facing image to determine an area of the item
12 from this vantage point, (2) a right facing reflection taking by
a first mirror 104A to determine an area from this vantage point,
(3) a left facing reflection taking by a second mirror 104B to
determine an area from this vantage point. The mirror set 104A, B
(generally, 104) is employed on the base 110, from a center of the
fixture 108 behind the item 12 being measured. The system then
parses out the front view, right facing reflection, and left facing
reflection to determine the area for each side. More specifically,
the system may parse the x, y, and z axis from the single image of
the item 12. In FIG. 4A, the system excludes the reflected images
by the mirrors 104 as part of the area (a1) calculation. In FIG.
4B, the image of the item reflected by the right mirror 104A is
considered for calculating area (a2). In FIG. 4C, the image of the
item reflected by the left mirror 104B is considered for
calculating area (a3). Thus, to provide a more accurate projection
of the actual volume of the item, the volume calculator 212
calculates an area of each of the three views, i.e., the front view
facing the camera 202 and the two views provided by the mirrors
104, and calculates an average of the three views to determine the
volume of the item 12. Also, the system determines the width of
each view of the item 12 and determines an average width to be used
as the depth. The average area is multiplied by the average depth
to calculate the volume.
[0051] In sum, the volume calculator 212 calculates the area of
each of the multiple views by pixel density, then averages the
three calculated areas together to determine an overall average
area of the item which takes into account the irregular shape of
the items.
[0052] For example, a front view of the bundle of bananas shown in
FIGS. 4A and 5A comprises an area (a1) having 15,000 pixels. A
second view shown in FIGS. 4B and 5B comprises an area (a2) having
14,500 pixels. A third view shown in FIGS. 4C and 5C comprises an
area (a3) having 18,000 pixels. The average area of the pixels of
the three viewed areas is 15,833 pixels, each pixel having a size
of 0.25 sq. mm., as established above, or 3958 sq. mm.
[0053] The volume calculator 212 also calculates a depth of the
item 12. Since the item 12 has varying depths at different heights,
an average depth is calculated with its corresponding average width
based on the average width of each side. The depth is determined by
perspective views, for example, shown in FIGS. 4A-4C, 5A-5C. For
example, a front view of an image of an item has a width and
height. If the item is rotated 90 degrees, then the width shown
from the front view is the depth of the rotated item. The processor
106 calculates the average width (w) from the three perspective
views (front, left, right), thereby determining the effective depth
of the item 12 to use in the volume calculation.
[0054] The volume calculator 212 determines the weighted average
width on each of the three image views, for example, referring
again to FIGS. 5A-C, by measuring the number of pixels it takes to
span the width (w) at one or more sections, or slices, of the image
views, then calculating an average width of each section (p), or
slice. FIGS. 5A-5C illustrate the measurement of width, and the
manner in which this is achieved is by performing a calculation
that averages the pixel length at each slice of width of the item
image. The measurement is the calculation of the average width, the
unit of measurement may be by in units of pixels (instead of mm or
inches). After the average width in number of pixels is generated,
by all the slices from all the sides may be averaged, and a
calculation may be performed to change the measurement from pixels
to mm or fraction thereof. In some embodiments, as shown in FIG. 5,
(w) and (p) are synonymous.
[0055] Referring again to FIGS. 4A and 5A, a section may be, on
average, 1600 pixels wide, or 400 mm (1600 pixels.times.0.25
mm/pixel). In FIGS. 4B and 5B, a section may be, on average, 1500
pixels wide, or 375 mm (1500 pixels.times.0.25 mm/pixel). In FIGS.
4C and 5C, a section may be, on average, 1800 pixels wide, or 450
mm (1800 pixels.times.0.25 mm/pixel). The volume calculator 212 may
calculate an average of the three average pixel widths (w) to
determine the average depth of the item. In this example: ((400
mm+375 mm+450 mm)/3)=408.33 mm.
[0056] The volume of the image of the item 12 is calculated by
multiplying the average area by the average depth. In the example
of FIGS. 4A-4C, it will be: [0057] Area=3,958 sq. mm. [0058]
Depth=408.33 mm. [0059] Volume=3,958 sq. mm.*408.33
mm.=1,616,170.15 cubic millimeters
[0060] At block 306, the item 12 is identified, for example, by the
optical recognition device 204.
[0061] At block 308, stored at the database 220 may include a
directory of items and a predetermined average weight per cubic
millimeter for each item. This information is stored in the
database 220, and at block 308 a database record can be accessed
for the known weight per cubic millimeter of bananas. In this
example, the average cubic millimeter weight of a banana is
0.00000324 pounds per cubic millimeter.
[0062] At block 310, the weight of the bananas can be determined.
The volume of the bananas shown in FIGS. 1 and 4A-4C can be
determined by multiplying the average weight (0.00000324 pounds per
cubic millimeter) by calculated volume (1,616,170.15 cubic
millimeters)=5.236 pounds.
[0063] In FIG. 5 the intent is to show that we are trying to
measure width, and the way we are going to do that is by averaging
the pixel length at each slice of width of the item.
[0064] For example if a camera has 1080p resolution, so it has 1080
pixels along the horizontal axis and 720 pixels along the vertical
axis, then the application would look at each of the 720 rows
(slices) and see if the item is present in that row, if it is
present in that row it would calculate how many of those 1080
horizontal pixels (width) are taken up by the item. Then it would
average all the widths together to come up with the average
width.
[0065] As will be appreciated by one skilled in the art, concepts
may be embodied as a device, system, method, or computer program
product. Accordingly, aspects may take the form of an entirely
hardware embodiment, an entirely software embodiment (including
firmware, resident software, micro-code, etc.) or an embodiment
combining software and hardware aspects that may all generally be
referred to herein as a "circuit," "module" or "system."
Furthermore, aspects may take the form of a computer program
product embodied in one or more computer readable medium(s) having
computer readable program code embodied thereon.
[0066] Computer program code for carrying out operations for the
concepts may be written in any combination of one or more
programming languages. The program code may execute entirely on the
user's computer, partly on the user's computer, as a stand-alone
software package, partly on the user's computer and partly on a
remote computer or entirely on the remote computer or server. In
the latter scenario, the remote computer may be connected to the
user's computer through any type of network, including a local area
network (LAN) or a wide area network (WAN), or the connection may
be made to an external computer (for example, through the Internet
using an Internet Service Provider).
[0067] Concepts are described herein with reference to flowchart
illustrations and/or block diagrams of methods, apparatus (systems)
and computer program products according to embodiments. It will be
understood that each block of the flowchart illustrations and/or
block diagrams, and combinations of blocks in the flowchart
illustrations and/or block diagrams, can be implemented by computer
program instructions. These computer program instructions may be
provided to a processor of a general purpose computer, special
purpose computer, or other programmable data processing apparatus
to produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or
blocks.
[0068] These computer program instructions may also be stored in a
computer readable medium that can direct a computer, other
programmable data processing apparatus, or other devices to
function in a particular manner, such that the instructions stored
in the computer readable medium produce an article of manufacture
including instructions which implement the function/act specified
in the flowchart and/or block diagram block or blocks.
[0069] The computer program instructions may also be loaded onto a
computer, other programmable data processing apparatus, cloud-based
infrastructure architecture, or other devices to cause a series of
operational steps to be performed on the computer, other
programmable apparatus or other devices to produce a computer
implemented process such that the instructions which execute on the
computer or other programmable apparatus provide processes for
implementing the functions/acts specified in the flowchart and/or
block diagram block or blocks.
[0070] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods and computer program products
according to various embodiments. In this regard, each block in the
flowchart or block diagrams may represent a module, segment, or
portion of code, which comprises one or more executable
instructions for implementing the specified logical function(s). It
should also be noted that, in some alternative implementations, the
functions noted in the block may occur out of the order noted in
the figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts, or combinations of special
purpose hardware and computer instructions.
[0071] While concepts have been shown and described with reference
to specific preferred embodiments, it should be understood by those
skilled in the art that various changes in form and detail may be
made therein without departing from the spirit and scope as defined
by the following claims.
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