CN110889842B - Method for detecting loose degree of small box cigarette labels - Google Patents
Method for detecting loose degree of small box cigarette labels Download PDFInfo
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- CN110889842B CN110889842B CN201911194928.7A CN201911194928A CN110889842B CN 110889842 B CN110889842 B CN 110889842B CN 201911194928 A CN201911194928 A CN 201911194928A CN 110889842 B CN110889842 B CN 110889842B
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Abstract
The application discloses a small box cigarette label looseness detection method, which comprises the steps of obtaining a toppling image of a small box cigarette label to be detected, carrying out image pretreatment on the toppling image to obtain a characteristic image corresponding to the toppling image, carrying out gray scale treatment on the characteristic image to obtain a gray scale image corresponding to the characteristic image, carrying out binarization treatment on the gray scale image to obtain a binarized image corresponding to the gray scale image, and obtaining a detection result whether the looseness of the small box cigarette label to be detected accords with a standard or not according to the binarized image. Therefore, the detection method of the loose degree of the small box cigarette label provided by the application can obtain the detection result whether the loose degree of the small box cigarette label to be detected meets the standard or not only needs to obtain the toppling image of the small box cigarette label to be detected after toppling, and carries out image pretreatment, gray level treatment and binarization treatment on the toppling image, but also can improve the detection efficiency of the loose degree of the small box cigarette label and ensure the detection accuracy rate.
Description
Technical Field
The application relates to the technical field of package detection, in particular to a method for detecting the loosening degree of a small box cigarette pack.
Background
The cigarette label is a trademark of the cigarette product and is commonly called as a cigarette case. The small box cigarette labels are usually stacked before packaging, and the small box cigarette labels are often loose due to insufficient distance between the cigarette labels or due to ink adhesion, so that when the cigarette labels are extracted from the packaging machine, the cigarette labels below can be taken away by the cigarette labels above, namely, the situation of multiple cigarettes exists in the single sucking process.
At present, the loose degree of the small box cigarette labels is mainly detected by adopting the artificial appearance in China, and the unqualified products with obviously insufficient loose cigarette labels are selected. However, the manual detection is easily affected by subjective consciousness, the accuracy of detection is difficult to guarantee, the efficiency of manual detection is low, and informationized management of product quality cannot be realized.
Disclosure of Invention
In order to solve the technical problems, the application provides a small box cigarette label looseness detection method, which can improve the detection efficiency of the small box cigarette label looseness and ensure the detection accuracy.
The application provides a method for detecting the looseness of a small box cigarette pack, which comprises the following steps:
acquiring a dumping image of a cigarette label of a small box to be detected;
performing image preprocessing on the dumping image to obtain a characteristic image corresponding to the dumping image;
carrying out gray processing on the characteristic image to obtain a gray image corresponding to the characteristic image;
performing binarization processing on the gray level image to obtain a binarization image corresponding to the gray level image;
and obtaining a detection result of whether the looseness of the cigarette label of the small box to be detected meets the standard or not according to the binarized image.
Preferably, the acquiring the dumping image of the cigarette label of the small box to be detected includes:
pouring the cigarette label of the small box to be detected to a fixed angle;
irradiating the poured small box cigarette label to be detected by a light source;
and acquiring a dumping image of the cigarette label of the small box to be detected by a camera.
Preferably, the image preprocessing is performed on the dumping image to obtain a feature image corresponding to the dumping image, including:
and carrying out one or more of image anomaly discrimination, image filtering, brightness correction, geometric correction and region-of-interest detection on the dumping image to obtain a characteristic image corresponding to the dumping image.
Preferably, the performing gray scale processing on the feature image to obtain a gray scale image corresponding to the feature image includes:
and replacing RGB (R, G, B) in the characteristic image with RGB (Gray, gray, gray) through a formula Gray= (R+G+B)/3, and obtaining a Gray image corresponding to the characteristic image.
Preferably, the binarizing processing is performed on the gray scale image to obtain a binarized image corresponding to the gray scale image, including:
and carrying out binarization processing on the gray level image, setting the gray level value of which the gray level value of all pixel points is smaller than or equal to a set binarization threshold value to 0, and setting the gray level value of the pixel points larger than the gray level value of the set binarization threshold value to 1, so as to obtain a binarization image corresponding to the gray level image.
Preferably, the obtaining, according to the binarized image, a detection result whether the looseness of the cigarette label of the small box to be detected meets a standard includes:
traversing each pixel point according to the binarized image, and counting the number of continuous pixel points with gray values of 1;
if the number of the continuous pixel points is larger than the set number threshold, judging that the looseness of the cigarette labels of the small boxes to be detected does not accord with the standard;
and if the condition that the number of the continuous pixel points is larger than the set number threshold value does not exist, judging that the looseness of the cigarette labels of the small boxes to be detected meets the standard.
Preferably, the light source is a strip light source, and the strip light source is located on the side face of the cigarette label of the small box to be detected.
Preferably, the camera is located directly above the small cigarette pack to be detected.
According to the small box cigarette label looseness detection method, the toppling image of the small box cigarette label to be detected is obtained, image preprocessing is carried out on the toppling image to obtain the characteristic image corresponding to the toppling image, gray processing is carried out on the characteristic image to obtain the gray image corresponding to the characteristic image, binarization processing is carried out on the gray image to obtain the binarization image corresponding to the gray image, and the detection result whether the looseness of the small box cigarette label to be detected meets the standard or not is obtained according to the binarization image. Therefore, according to the small box cigarette label looseness detection method provided by the embodiment of the application, the detection result of whether the looseness of the small box cigarette label to be detected meets the standard can be obtained only by acquiring the toppling image of the small box cigarette label to be detected after toppling, and performing image pretreatment, gray level treatment and binarization treatment on the toppling image.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
Fig. 1 is a schematic flow chart of a method for detecting the loose degree of a small box cigarette label according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another method for detecting the loose degree of a small box cigarette pack according to an embodiment of the present application.
Detailed Description
In order to make the technical solution of the present application better understood by those skilled in the art, the technical solution of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments.
It will be understood that when an element is referred to as being "fixed" or "disposed" on another element, it can be directly on the other element or be indirectly on the other element; when an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element.
It is to be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are merely for convenience in describing and simplifying the description based on the orientation or positional relationship shown in the drawings, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus are not to be construed as limiting the application.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of a plurality of "a number" is two or more, unless explicitly defined otherwise.
It should be understood that the structures, proportions, sizes, etc. shown in the drawings are for illustration purposes only and should not be construed as limiting the application to the extent that it can be practiced, since modifications, changes in the proportions, or otherwise, used in the practice of the application, are not intended to be critical to the essential characteristics of the application, but are intended to fall within the spirit and scope of the application.
As described in the background section, if the loose degree of the small cigarette pack is not good, the lower cigarette pack can be taken away by the upper cigarette pack when the cigarette pack is extracted on the packaging machine, namely, the condition of multiple holding exists in the single sucking process.
In view of the above, the present application provides a method for detecting the loose degree of a small cigarette pack, referring to fig. 1, in which the method for detecting the loose degree of a small cigarette pack according to the embodiment of the present application includes:
s110, acquiring a dumping image of the cigarette label of the small box to be detected.
It should be noted that, under the condition of good looseness, the stacked small cigarette labels should have a certain distance and be uniformly distributed between the cigarette labels after being poured. Therefore, the loosening condition of the small box cigarette label can be detected by detecting the side surface state of the small box cigarette label after pouring.
In this embodiment, a dumping image of the small box of cigarettes to be detected after dumping can be obtained through the image acquisition device, wherein the obtained dumping image is a color image.
S120, performing image preprocessing on the dumping image to obtain a characteristic image corresponding to the dumping image.
In this embodiment, since the obtained dumping image includes image noise, an image with abnormal shooting, and the like, the image with abnormal shooting needs to be identified and denoised, and the dumping image may be preprocessed by frequency domain filtering, so as to obtain a feature image corresponding to the dumping image.
S130, gray processing is carried out on the characteristic image, and a gray image corresponding to the characteristic image is obtained.
In this embodiment, in order to reflect morphological features of the image, gray processing is performed on the feature image, so as to obtain a gray image corresponding to the feature image, so as to prepare for further image analysis.
And S140, performing binarization processing on the gray level image to obtain a binarized image corresponding to the gray level image.
In this embodiment, binarization processing is performed on the gray level image, so as to obtain a binarized image corresponding to the gray level image, thereby improving the efficiency of image recognition.
And S150, obtaining a detection result of whether the looseness of the cigarette label of the small box to be detected meets the standard or not according to the binarized image.
As can be seen from the above, in the method for detecting the loose degree of the small box cigarette label provided by the embodiment of the application, the toppling image of the small box cigarette label to be detected is obtained, the toppling image is subjected to image preprocessing to obtain the characteristic image corresponding to the toppling image, the characteristic image is subjected to gray processing to obtain the gray image corresponding to the characteristic image, the gray image is subjected to binarization processing to obtain the binarization image corresponding to the gray image, and the detection result whether the loose degree of the small box cigarette label to be detected accords with the standard is obtained according to the binarization image. Therefore, according to the small box cigarette label looseness detection method provided by the embodiment of the application, the detection result of whether the looseness of the small box cigarette label to be detected meets the standard can be obtained only by acquiring the toppling image of the small box cigarette label to be detected after toppling, and performing image pretreatment, gray level treatment and binarization treatment on the toppling image.
Referring to fig. 2, another flow chart of a method for detecting the loose degree of a small cigarette packet according to an embodiment of the present application includes:
s210, pouring the cigarette label of the small box to be detected to a fixed angle.
In this embodiment, in order to ensure the accuracy of the loosening degree detection result, the device such as the motor driving rotary cylinder may be used to enable the small box cigarette label to be dumped to a fixed angle each time. Wherein, this fixed angle is preset, can confirm through many experiments.
S220, irradiating the poured small box cigarette label to be detected by a light source.
In this embodiment, in order to obtain a clear image conveniently, after the small box cigarette label to be detected is dumped to a fixed angle, the dumped small box cigarette label to be detected is irradiated by a light source.
Specifically, the light source is a strip light source and is positioned on the side surface of the cigarette label of the small box to be detected. The strip-shaped light source positioned on the side face of the small box cigarette label to be detected can enable the acquired side face image to be clearer, and the detection of the side face state of the small box cigarette label after dumping is convenient.
S230, acquiring a dumping image of the cigarette label of the small box to be detected by a camera.
In this embodiment, after the light source irradiates the poured small box cigarette label to be detected, a camera is used to obtain a pouring image of the small box cigarette label to be detected.
Specifically, the camera is positioned right above the cigarette label of the small box to be detected. The camera positioned right above the small box cigarette label to be detected can ensure that the collected dumping image is a complete dumping image of the small box cigarette label, and the distance between the small box cigarette labels is conveniently identified.
S240, performing image preprocessing on the dumping image to obtain a characteristic image corresponding to the dumping image.
S250, gray processing is carried out on the characteristic image, and a gray image corresponding to the characteristic image is obtained.
S260, performing binarization processing on the gray level image to obtain a binarized image corresponding to the gray level image
S270, according to the binarized image, a detection result of whether the looseness of the cigarette label of the small box to be detected meets the standard is obtained.
Specifically, based on the foregoing embodiment, in one embodiment of the present application, image preprocessing is performed on a dumping image to obtain a feature image corresponding to the dumping image, which specifically includes:
and carrying out one or more of image anomaly discrimination, image filtering, brightness correction, geometric correction and region-of-interest detection on the dumping image to obtain a characteristic image corresponding to the dumping image.
In this embodiment, the image preprocessing may be performed on the toppled image by using frequency domain filtering, such as image anomaly discrimination, image filtering, brightness correction, geometric correction, region of interest detection, and the like, so as to perform general denoising and reduce the signal intensity of moire.
Further, on the basis of the foregoing embodiment, in one embodiment of the present application, gray processing is performed on a feature image to obtain a gray image corresponding to the feature image, which specifically includes:
and replacing RGB (R, G, B) in the characteristic image with RGB (Gray, gray, gray) through a formula Gray= (R+G+B)/3, so as to obtain a Gray image corresponding to the characteristic image.
In this embodiment, in order to balance that the components of the RGB three channels have the same weight, the formula gray= (r+g+b)/3 is adopted, and RGB (R, G, B) in the feature image is replaced by RGB (Gray ), so as to obtain the Gray image corresponding to the feature image. Wherein Gray represents the Gray value of the Gray image, R represents the red pixel value in each pixel in the surface image, G represents the green pixel value in each pixel in the surface image, and B represents the blue pixel value in each pixel in the surface image.
Further, on the basis of the above embodiment, in one embodiment of the present application, binarizing the gray-scale image to obtain a binarized image corresponding to the gray-scale image, including:
and carrying out binarization processing on the gray image, setting the gray value of which the gray value of all pixel points is smaller than or equal to the set binarization threshold value to 0 and setting the gray value of which the gray value of the pixel points is larger than the set binarization threshold value to 1, so as to obtain the binary image corresponding to the gray image.
In this embodiment, the binarization processing may be performed on the gray image by using Otsu binarization, where the gray value of all the pixel points with gray values smaller than or equal to the set binarization threshold is set to 0, and the gray value of the pixel points with gray values greater than the set binarization threshold is set to 1, so as to obtain the binary image corresponding to the gray image. The binarization threshold value is preset and can be adjusted according to multiple test results.
Further, based on the above embodiment, in one embodiment of the present application, according to the binarized image, a detection result of whether the looseness of the cigarette label of the small box to be detected meets the standard is obtained, including:
traversing each pixel point according to the binarized image, and counting the number of continuous pixel points with gray values of 1;
if the number of the continuous pixel points is larger than the set number threshold, judging that the looseness of the cigarette labels of the small boxes to be detected does not accord with the standard;
if the condition that the number of the continuous pixel points is larger than the set number threshold value does not exist, judging that the looseness of the cigarette labels of the small boxes to be detected meets the standard.
In this embodiment, since the side profile of the small box cigarette label is darker in the obtained dumping image, the gray value of the pixel point in the area where the small box cigarette label is located is set to 1 in the obtained binarized image. By traversing each pixel point and counting the number of the pixel points in the continuous rows or the pixel points in the continuous columns with the gray value of 1, the situation that the small box cigarette labels are adhered to cause poor looseness can be identified. Specifically, if the number of the pixel points in the continuous rows or the pixel points in the continuous columns is larger than a set number threshold, judging that the looseness of the cigarette labels of the small boxes to be detected does not meet the standard; if the condition that the number of the continuous pixel points is larger than the set number threshold value does not exist, judging that the looseness of the cigarette labels of the small boxes to be detected meets the standard.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. The method for detecting the loose degree of the small box cigarette labels is characterized by comprising the following steps of:
acquiring a dumping image of a cigarette label of a small box to be detected;
performing image preprocessing on the dumping image to obtain a characteristic image corresponding to the dumping image;
carrying out gray processing on the characteristic image to obtain a gray image corresponding to the characteristic image;
performing binarization processing on the gray level image to obtain a binarization image corresponding to the gray level image;
according to the binarized image, a detection result of whether the looseness of the cigarette label of the small box to be detected meets the standard is obtained, and the detection result comprises the following steps:
traversing each pixel point according to the binarized image, and counting the number of continuous pixel points with gray values of 1;
if the number of the continuous pixel points is larger than the set number threshold, judging that the looseness of the cigarette labels of the small boxes to be detected does not accord with the standard;
and if the condition that the number of the continuous pixel points is larger than the set number threshold value does not exist, judging that the looseness of the cigarette labels of the small boxes to be detected meets the standard.
2. The method of claim 1, wherein the acquiring a dumping image of a packet of cigarettes to be detected comprises:
pouring the cigarette label of the small box to be detected to a fixed angle;
irradiating the poured small box cigarette label to be detected by a light source;
and acquiring a dumping image of the cigarette label of the small box to be detected by a camera.
3. The method according to claim 1, wherein the performing image preprocessing on the dumping image to obtain a feature image corresponding to the dumping image includes:
and carrying out one or more of image anomaly discrimination, image filtering, brightness correction, geometric correction and region-of-interest detection on the dumping image to obtain a characteristic image corresponding to the dumping image.
4. A method according to claim 3, wherein said subjecting the feature image to gray scale processing to obtain a gray scale image corresponding to the feature image comprises:
and replacing RGB (R, G, B) in the characteristic image with RGB (Gray, gray, gray) through a formula Gray= (R+G+B)/3, and obtaining a Gray image corresponding to the characteristic image.
5. The method according to claim 4, wherein the binarizing the gray-scale image to obtain a binarized image corresponding to the gray-scale image comprises:
and carrying out binarization processing on the gray level image, setting the gray level value of which the gray level value of all pixel points is smaller than or equal to a set binarization threshold value to 0, and setting the gray level value of the pixel points larger than the gray level value of the set binarization threshold value to 1, so as to obtain a binarization image corresponding to the gray level image.
6. The method of claim 2, wherein the light source is a strip light source and the strip light source is located on a side of the pouch label to be inspected.
7. The method of claim 6, wherein the camera is located directly above the pouch label to be detected.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6369912B1 (en) * | 1998-01-23 | 2002-04-09 | Minolta Co., Ltd. | Image processing apparatus capable of applying line component to image |
| CN101109712A (en) * | 2007-07-13 | 2008-01-23 | 广西中烟工业公司 | Detecting device for defect of cigarette packer small box aluminum foil paper |
| CN109215048A (en) * | 2018-09-21 | 2019-01-15 | 云南中烟工业有限责任公司 | Pipe tobacco length determining method and system based on machine vision |
| CN109522767A (en) * | 2017-09-18 | 2019-03-26 | 北京星河泰视特科技有限公司 | One-dimension code short in size visual detection algorithm |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003081446A (en) * | 2001-09-12 | 2003-03-19 | Sharp Corp | Cassette with size detecting function |
-
2019
- 2019-11-28 CN CN201911194928.7A patent/CN110889842B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6369912B1 (en) * | 1998-01-23 | 2002-04-09 | Minolta Co., Ltd. | Image processing apparatus capable of applying line component to image |
| CN101109712A (en) * | 2007-07-13 | 2008-01-23 | 广西中烟工业公司 | Detecting device for defect of cigarette packer small box aluminum foil paper |
| CN109522767A (en) * | 2017-09-18 | 2019-03-26 | 北京星河泰视特科技有限公司 | One-dimension code short in size visual detection algorithm |
| CN109215048A (en) * | 2018-09-21 | 2019-01-15 | 云南中烟工业有限责任公司 | Pipe tobacco length determining method and system based on machine vision |
Non-Patent Citations (1)
| Title |
|---|
| 林明星 等.跳汰机床层松散度的计算机检测系统.煤矿机电.2007,9-11. * |
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