CN102013019A - Information image recognition system and method - Google Patents
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Abstract
The invention relates to an information image recognition system and an information image recognition method. The information image recognition system comprises a plurality of fixed focus cameras at different depths of field, and a plurality of processors connected with the plurality of fixed focus cameras, wherein the depths of field of the plurality of fixed focus cameras are superposed to form the total depth of field, and each fixed focus camera shoots an information image in the region of the total depth of field; and the processors compare the definition of a plurality of shot information images to acquire the information image with the highest definition, and decode and recognize the information image with the highest definition. In the information image recognition system and the information image recognition method, the plurality of fixed focus cameras at different depths of field are collected; each camera shoots the information image in the region of the total depth of field; and the processers compare the definition of the plurality of information images to acquire the information image with the highest definition, and decode and recognize the information image; therefore, a distinct image can be acquired without adjustment of the focus, the image is well recognized, and the adjustment time is saved.
Description
[ technical field ] A method for producing a semiconductor device
The present invention relates to the field of image recognition, and in particular, to an information image recognition system and method.
[ background of the invention ]
In the market, various articles are provided with bar codes, and bar codes are scanned and identified by a bar code scanner, so that information related to the articles, such as prices, can be inquired according to the bar codes.
The traditional image recognition equipment comprises fixed focus recognition and zooming recognition, wherein the fixed focus recognition adopts a special fixed focus scanning lens, the depth of field of scanning is limited, a scanned object can be easily recognized in a clear area, but the scanned object is in a fuzzy area, and a large amount of software algorithms are needed to improve the recognizability of the image; zooming recognition adopts a zoom lens to adjust a lens to change the focal length so as to recognize an object, but the adjustment time is long, and an adjustment mechanism is too complex.
[ summary of the invention ]
Accordingly, there is a need for an information image recognition system that can better recognize an image without adjusting the focal length and save the adjustment time.
An information image recognition system comprises
The system comprises a plurality of fixed-focus cameras with different depth of field, wherein the depth of field of the fixed-focus cameras is superposed into an overall depth of field, and each fixed-focus camera shoots an information image in the overall depth of field area;
and the processor is connected with the fixed-focus cameras and is used for comparing the definition of the plurality of shot information images to obtain an information image with the highest definition and decoding and identifying the information image with the highest definition.
Preferably, the system further comprises a switching circuit respectively connected with the plurality of fixed-focus cameras and the processor, and after the processor obtains the information image with the highest definition, the switching circuit is controlled to switch to the picture shot by the camera shooting the information image with the highest definition.
Preferably, the fixed-focus camera is a computer camera, a mobile phone camera or a pinhole camera.
Preferably, the number of the fixed-focus cameras is 3.
Preferably, the 3 fixed-focus cameras are arranged in a finished product font or a straight font.
In addition, it is necessary to provide an information image recognition method, which can better recognize an image without adjusting a focal length and save an adjustment time.
An information image recognition method, comprising the steps of:
a plurality of fixed-focus cameras with different depth of field are adopted, the depth of field of the fixed-focus cameras is superposed to form an overall depth of field, and each fixed-focus camera shoots an information image in the overall depth of field area;
and comparing the definition of the plurality of shot information images to obtain an information image with the highest definition, and decoding and identifying the information image with the highest definition.
Preferably, the method further comprises the step of setting a switching circuit and controlling the switching circuit to switch the picture shot by the camera which shoots the information image with the highest definition.
Preferably, the fixed-focus camera is a computer camera, a mobile phone camera or a pinhole camera.
Preferably, the number of the fixed-focus cameras is 3.
Preferably, the 3 fixed-focus cameras are arranged in a finished product font or a straight font.
According to the information image identification system and method, the plurality of fixed-focus cameras are collected, each camera shoots an information image in the total depth of field area, the information images with the highest definition are obtained through the definition comparison of the plurality of information images by the processor, the obtained information images are decoded and identified, the focal length does not need to be adjusted, clear images can be obtained, better identification images can be obtained, and the adjustment time is saved.
[ description of the drawings ]
FIG. 1 is a schematic diagram of an information image recognition system according to an embodiment;
FIG. 2 is a schematic diagram of the distribution of three cameras in one embodiment;
fig. 3 is a schematic diagram of the shooting areas of the three cameras in fig. 2.
[ detailed description ] embodiments
The following describes the technical solution in detail with reference to specific embodiments.
As shown in fig. 1, in one embodiment, an information image recognition system includes a plurality of fixed-focus cameras 10 with different depths of field, and a processor 20. Wherein,
the depths of field of the fixed-focus cameras 10 with different depths of field are superposed to form an overall depth of field, and each fixed-focus camera 10 shoots an information image in the overall depth of field area. Each camera 10 may photograph an image within a certain range, i.e., a depth area, and the photographed area may be divided into a clear area and a blurred area. The plurality of fixed-focus cameras 10 are arranged together, the depth of field of the fixed-focus cameras is overlapped to form the total depth of field, and the shooting range is large. When a shot object enters a total depth-of-field area formed by overlapping the depths of field of the multiple fixed-focus cameras 10, the multiple fixed-focus cameras 10 shoot the object to shoot an information image, but the clear areas of the shot images of the multiple cameras 10 are different, so that when the object enters the total depth-of-field area, the information images shot by the multiple cameras 10 are different in definition, and the information image shot by one camera is always clear. The plurality of fixed-focus cameras can be arranged into circles, regular polygons, straight lines and the like, and can also be arranged into triangles. A plurality of fixed focus cameras are arranged into a circle and are distributed uniformly and symmetrically. The plurality of fixed-focus cameras are arranged in a linear shape, and the total field depth area is large. The information image is an image containing identifiable effective information, such as a one-bit barcode image, a two-dimensional barcode image or a black mark image. The fixed-focus camera can be a computer camera, a mobile phone camera or a common camera such as a pinhole camera. The plurality of fixed-focus cameras adopt a plurality of fixed-focus cameras with different focal lengths, the depth of field is different, and the range of recognizable clear images is wide. Depth of field refers to the range of object distances measured in front of the camera lens or other imager along the camera axis of the imaging depth camera that enables a sharp image to be taken.
The processor 20 is connected to the plurality of fixed-focus cameras 10, receives the information images shot by the plurality of fixed-focus cameras 10, compares the sharpness of the plurality of information images to obtain an information image with the highest sharpness, and decodes and identifies the information image with the highest sharpness. Because the depth of field of each camera 10 is limited, in the total depth of field area, the information images shot by each fixed-focus camera 10 have different definitions, and the processor 20 compares and analyzes the information images shot by the plurality of fixed-focus cameras 10 to obtain the information image with the highest definition as the required information image. The processor 20 then identifies the obtained information image with the highest definition, the operation is simple and convenient, a large amount of software methods are not needed for repairing the blurred image, the focal length is not needed to be adjusted, and the adjustment time is saved.
In this embodiment, the information image recognition system further includes a switching circuit 30. The switching circuit 30 is connected to each of the plurality of fixed-focus cameras 10 and the processor 20. After the processor 20 obtains the information image with the highest resolution, the switching circuit 30 is controlled to switch the picture shot by the camera 10 connected to the information image with the highest resolution. After the processor 20 compares the information images with the highest resolution, the switching circuit 30 switches the connection to the camera 10 for shooting the information image with the highest resolution to the picture shot by the camera 10.
Taking 300 mm depth of field shooting as an example, 3 common fixed-focus cameras with different depth of field are adopted, and the total depth of field area is 300 mm. Fig. 2 shows the distribution of three fixed-focus cameras. The 3 ordinary fixed-focus cameras are distributed in a delta shape and can also be in a straight shape. Fig. 3 is a schematic diagram of the distribution of the regions shot by the three cameras, in which the shooting region of the camera 12 is divided into a clear region 120 and a blur region 122, the shooting region of the camera 14 is divided into a clear region 140, blur regions 142 and 144, and the shooting region of the camera 16 is divided into a clear region 160, blur regions 162 and 164. Where zones 120, 142 have overlapping portions, zones 122, 140, 162 have overlapping portions, and zones 144 and 160 have overlapping portions. The shot object is located in a 300-millimeter depth area, the three cameras can shoot the object, when the object is located in the area 120, the information image shot by the camera 12 is clearest, when the object is located in the area 140, the information image shot by the camera 14 is clearest, when the object is located in the area 160, the information image shot by the camera 16 is clearest, no matter where the object is located in the 300-millimeter depth area, the processor 20 compares the definitions of the information images shot by the cameras 12, 14 and 16 to obtain the information image with the highest definition, and then decodes and identifies the information image with the highest definition.
In addition, the number of the fixed-focus cameras can be set according to the depth of field.
In one embodiment, an information image recognition method includes the steps of:
A. a plurality of fixed-focus cameras with different depth of field are adopted, the depth of field of the fixed-focus cameras is superposed to form the total depth of field, and each fixed-focus camera shoots an information image in the total depth of field area.
In step a, each camera 10 can shoot an image within a certain range, i.e., a depth area, and the shot area can be divided into a clear area and a blurred area. The plurality of fixed-focus cameras 10 are arranged together, the depth of field of the fixed-focus cameras is overlapped to form the total depth of field, and the shooting distance is large. When a shot object enters a total depth-of-field area formed by overlapping the depths of field of the multiple fixed-focus cameras 10, the multiple fixed-focus cameras 10 shoot the object to shoot an information image, but the clear areas of the shot images of the multiple cameras 10 are different, so that when the object enters the total depth-of-field area, the information images shot by the multiple cameras 10 are different in definition, and the information image shot by one camera is always clear. The plurality of fixed-focus cameras can be arranged into circles, regular polygons, straight lines and the like, and can also be arranged into triangles. A plurality of fixed focus cameras are arranged into a circle and are distributed uniformly and symmetrically. The plurality of fixed-focus cameras are arranged in a linear shape, and the total field depth area is large. The information image is an image containing identifiable effective information, such as a one-bit barcode image, a two-dimensional barcode image or a black mark image. The fixed-focus camera can be a computer camera, a mobile phone camera or a common camera such as a pinhole camera. The plurality of fixed-focus cameras adopt a plurality of fixed-focus cameras with different focal lengths, the depth of field is different, and the range of recognizable clear images is wide. Depth of field refers to the range of object distances measured in front of the camera lens or other imager along the camera axis of the imaging depth camera that enables a sharp image to be taken. In this embodiment, when the depth of field is 300 millimeters, a plurality of fixed focus cameras are 3, can satisfy the demand, and three cameras are arranged and are article font or a font. The number of cameras is related to the depth of field.
B. And comparing the definition of the plurality of shot information images to obtain an information image with the highest definition, and decoding and identifying the information image with the highest definition.
In the step B, since the depth of field of each camera 10 is limited, in the total depth of field region, the information images shot by each fixed-focus camera 10 have different definitions, and the processor 20 performs comparison and analysis on the information images shot by the plurality of fixed-focus cameras 10 to obtain the information image with the highest definition as the required information image. The processor 20 then identifies the obtained information image with the highest definition, the operation is simple and convenient, a large amount of software methods are not needed for repairing the blurred image, the focal length is not needed to be adjusted, and the adjustment time is saved.
The information image identification method further comprises the step of setting a switching circuit after the step B, and controlling the switching circuit to switch and connect to the picture shot by the camera shooting the information image with the highest definition. After the processor 20 obtains the information image with the highest resolution, the switching circuit 30 is controlled to switch the picture shot by the camera 10 connected to the information image with the highest resolution. After the processor 20 compares the information images with the highest resolution, the switching circuit 30 switches the camera connected to the information image with the highest resolution to the picture shot by the camera.
According to the information image identification system and method, the plurality of fixed-focus cameras are collected, each camera shoots an information image in the total depth of field area, the information images with the highest definition are obtained through the definition comparison of the plurality of information images by the processor, the obtained information images are decoded and identified, the focal length does not need to be adjusted, clear images can be obtained, better identification images can be obtained, and the adjustment time is saved.
In addition, the camera adopts a common camera, so that the cost is reduced.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. An information image recognition system, comprising
The system comprises a plurality of fixed-focus cameras with different depth of field, wherein the depth of field of the fixed-focus cameras is superposed into an overall depth of field, and each fixed-focus camera shoots an information image in the overall depth of field area;
and the processor is connected with the fixed-focus cameras and is used for comparing the definition of the plurality of shot information images to obtain an information image with the highest definition and decoding and identifying the information image with the highest definition.
2. The information image recognition system according to claim 1, further comprising a switching circuit connected to each of the plurality of fixed-focus cameras and the processor, wherein the processor controls the switching circuit to switch to a picture taken by the camera taking the information image with the highest resolution after obtaining the information image with the highest resolution.
3. The information image recognition system of claim 1, wherein the fixed-focus camera is a computer camera, a mobile phone camera, or a pinhole camera.
4. The information image recognition system according to claim 1, wherein the plurality of fixed-focus cameras is 3.
5. The information image recognition system of claim 1, wherein the 3 fixed-focus cameras arrange a finished glyph or a glyph in line.
6. An information image recognition method, comprising the steps of:
a plurality of fixed-focus cameras with different depth of field are adopted, the depth of field of the fixed-focus cameras is superposed to form an overall depth of field, and each fixed-focus camera shoots an information image in the overall depth of field area;
and comparing the definition of the plurality of shot information images to obtain an information image with the highest definition, and decoding and identifying the information image with the highest definition.
7. The information image recognition method according to claim 6, characterized in that: the method also comprises a step of setting a switching circuit and controlling the switching circuit to switch and connect to the picture shot by the camera shooting the information image with the highest definition.
8. The information image recognition method according to claim 6, characterized in that: the fixed-focus camera is a computer camera, a mobile phone camera or a pinhole camera.
9. The information image recognition method according to claim 6, wherein the plurality of fixed-focus cameras is 3.
10. The information image recognition method of claim 9, wherein the 3 fixed-focus cameras arrange a finished font or a straight font.
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| CN 201010573433 CN102013019A (en) | 2010-12-03 | 2010-12-03 | Information image recognition system and method |
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| CN 201010573433 CN102013019A (en) | 2010-12-03 | 2010-12-03 | Information image recognition system and method |
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| CN104349063A (en) * | 2014-10-27 | 2015-02-11 | 东莞宇龙通信科技有限公司 | Method, device and terminal for controlling camera shooting |
| CN105450931A (en) * | 2015-12-30 | 2016-03-30 | 联想(北京)有限公司 | Imaging method and device based on array cameras, and electronic equipment |
| CN106713761A (en) * | 2017-01-11 | 2017-05-24 | 中控智慧科技股份有限公司 | Image processing method and apparatus |
| CN109376566A (en) * | 2018-12-12 | 2019-02-22 | 福州金典工业产品设计有限公司 | Reading code wall and its setting method based on array camera |
| CN109409147A (en) * | 2017-08-16 | 2019-03-01 | 中兴通讯股份有限公司 | A kind of bar code recognition and device |
| CN109559454A (en) * | 2017-09-27 | 2019-04-02 | 缤果可为（北京）科技有限公司 | Cash method and self-service cashier based on neural network recognization commodity |
| CN109831617A (en) * | 2017-11-23 | 2019-05-31 | 姜鹏飞 | A kind of mobile device and operating system |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104349063A (en) * | 2014-10-27 | 2015-02-11 | 东莞宇龙通信科技有限公司 | Method, device and terminal for controlling camera shooting |
| CN105450931A (en) * | 2015-12-30 | 2016-03-30 | 联想(北京)有限公司 | Imaging method and device based on array cameras, and electronic equipment |
| CN105450931B (en) * | 2015-12-30 | 2019-04-26 | 联想(北京)有限公司 | A kind of imaging method based on array camera, device and electronic equipment |
| CN106713761A (en) * | 2017-01-11 | 2017-05-24 | 中控智慧科技股份有限公司 | Image processing method and apparatus |
| CN109409147B (en) * | 2017-08-16 | 2023-08-08 | 中兴通讯股份有限公司 | Bar code recognition method and device |
| CN109409147A (en) * | 2017-08-16 | 2019-03-01 | 中兴通讯股份有限公司 | A kind of bar code recognition and device |
| CN109559457B (en) * | 2017-09-27 | 2021-09-21 | 缤果可为（北京）科技有限公司 | Neural network-based commodity identification cash registering method and self-service cash registering desk |
| CN109559454A (en) * | 2017-09-27 | 2019-04-02 | 缤果可为（北京）科技有限公司 | Cash method and self-service cashier based on neural network recognization commodity |
| CN109559457A (en) * | 2017-09-27 | 2019-04-02 | 缤果可为（北京）科技有限公司 | Cash method and self-service cashier based on neural network recognization commodity |
| CN109559458A (en) * | 2017-09-27 | 2019-04-02 | 缤果可为（北京）科技有限公司 | Cash method and self-service cashier based on neural network recognization commodity |
| CN109559458B (en) * | 2017-09-27 | 2021-09-21 | 缤果可为（北京）科技有限公司 | Neural network-based commodity identification cash registering method and self-service cash registering desk |
| CN109831617A (en) * | 2017-11-23 | 2019-05-31 | 姜鹏飞 | A kind of mobile device and operating system |
| CN109376566A (en) * | 2018-12-12 | 2019-02-22 | 福州金典工业产品设计有限公司 | Reading code wall and its setting method based on array camera |
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Application publication date: 20110413 |