CN201028984Y - Automatic color recognition system - Google Patents
Automatic color recognition system Download PDFInfo
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- CN201028984Y CN201028984Y CNU2006201062773U CN200620106277U CN201028984Y CN 201028984 Y CN201028984 Y CN 201028984Y CN U2006201062773 U CNU2006201062773 U CN U2006201062773U CN 200620106277 U CN200620106277 U CN 200620106277U CN 201028984 Y CN201028984 Y CN 201028984Y
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- 239000003086 colorant Substances 0.000 claims abstract description 17
- 230000005540 biological transmission Effects 0.000 abstract description 2
- 208000036693 Color-vision disease Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000019771 cognition Effects 0.000 description 1
- 201000007254 color blindness Diseases 0.000 description 1
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Abstract
The utility model discloses an automatic color identifying system that consists of a color picking device, a RGB acquisition module, a color identifying module and an output display module. The color picking device sends color signals to the RGB acquisition module which sends the acquired color value to the color identifying module that sends the identified color to the output display module for displaying. The color picking device consists of a dark box, a videography module and a color source picking hole. The videography module is arranged inside the dark box, while the color source picking hole is arranged on one surface of the dark box. The utility model sends the content obtained by the camera to a computer through USB transmission line and obtains RGB value through a software module and then automatically identifies the color according to the obtained RGB value and the corresponding relationship with colors. The utility model can be used for automatically identifying the types and models of the goods by adopting specific colors for specific goods. The utility model has the advantages of low cost and convenient operation.
Description
[technical field]
The utility model relates to logistics management, relates in particular to the color automatic identification technology in the logistics management.
[background technology]
Often need discern the goods of different classes of or model in the logistics management, most at present employing bar codes, numbering, color etc. are discerned.
The technology of employing bar code recognition is comparative maturity, but cost is higher.That adopts numbering identification can only lean on manual observation, and efficient is low, makes mistakes easily.That adopts color identification does not also have widespread use at present, all is to adopt artificial cognition yet, and efficient is low, make mistakes easily, and the people of colour blindness can't operate at all.
So, how color-coded on the goods discerned automatically, judge the classification or the model of goods by the identification of color, and cost is low, becomes the important topic of those skilled in the art's research.
[summary of the invention]
The purpose of this utility model solves the problems of the prior art exactly, proposes a kind of colors automatic recognizing system, can discern color-coded on the goods automatically, and to distinguish the classification or the model of goods, cost is low.
For achieving the above object, the utility model proposes a kind of colors automatic recognizing system, comprise adopting look device, RGB acquisition module, color identification module and exporting display module of connecting successively, the described look device output chrominance signal of adopting is given the RGB acquisition module, the RGB acquisition module is exported to the color identification module with the color numerical value that obtains, and the color identification module is exported to the output display module with the color that identifies and shown.
As preferably, the described look device of adopting comprises that camera bellows, camera assembly and look source gather the hole, and described camera assembly is arranged in the camera bellows, and the look source is gathered the hole and is arranged on the face of camera bellows.
As preferably, described camera assembly comprises camera, removable flat board, support and output line, and described camera is placed on the removable flat board, and stent support is below removable flat board, the output terminal of camera is connected with output line, and described output line transfers data to the RGB acquisition module.
The beneficial effects of the utility model: the utility model is sent to the content of camera picked-up in the computer by the USB transmission line, obtains rgb value by software module again, according to the corresponding relation of rgb value that is obtained and color, color is discerned automatically.Specific goods adopts specific color, like this, just can discern automatically cargo type or model easily in the logistics management field.The utility model realizes that cost is low, easy to operate.
Feature of the present utility model and advantage will be elaborated in conjunction with the accompanying drawings by embodiment.
[description of drawings]
Fig. 1 is the structural representation of a kind of colors automatic recognizing system of the utility model;
Fig. 2 is a structural representation of adopting the look device in a kind of colors automatic recognizing system of the utility model.
[embodiment]
Fig. 1 is the structural representation of a kind of colors automatic recognizing system of the utility model.Comprise adopting look device 1, RGB acquisition module 2, color identification module 3 and exporting display module 4 of connecting successively, the described look device 1 output chrominance signal of adopting is given RGB acquisition module 2, RGB acquisition module 2 is exported to color identification module 3 with the color numerical value that obtains, and color identification module 3 is exported to output display module 4 with the color that identifies and shown.The described look device 1 of adopting comprises camera bellows 11, camera assembly 12 and collection hole 13, look source, and described camera assembly 12 is arranged in the camera bellows 11, and the look source is gathered hole 13 and is arranged on the face of camera bellows 11.Described camera assembly 12 comprises camera 121, removable dull and stereotyped 122, support 123 and output line 124, described camera 121 is placed on removable dull and stereotyped 122, support 123 be supported on removable dull and stereotyped 122 below, the output terminal of camera 121 is connected with output line 124, and described output line 124 transfers data to RGB acquisition module 2.
Fig. 2 is a structural representation of adopting the look device in a kind of colors automatic recognizing system of the utility model.Camera 121 obtains outside colouring information and sends in the computer by USB interface, adopts RGB acquisition module 2 to obtain the rgb value of current color information in real time, proposes a color system at this system, whole colour gamut is divided into 512 parts, and is numbered.According to experimental result these 512 color codes are assigned to ten kinds of common colors, reach ten kinds of common colors of color identification by color identification module 3 at last, again the color that identifies is shown to the user by output display module 4.
Camera 121 is clipped on removable dull and stereotyped 122, moving removable dull and stereotyped 122 makes cam lens gather about the 13 about 60mm of hole apart from the look source, the light source of system be the LED lamp that carries of camera in order to avoid the high light part of its reflection, cam lens is upwards raised about 20 °.Camera 121 is received on the computer by output line 124.Because rgb value is subject to the influence of extraneous light intensity,, adopt camera bellows 11 that imaging environment and external environment is isolated for reducing the influence that this error causes system.Adopt the some points on the uniform relatively zone of brightness to get RGB, weighted mean obtains final rgb value then.
Chromaticity coordinate figure rgb and tristimulus values RGB dual mode are arranged in the differentiation of color.Wherein
If use chromaticity coordinates value rgb to distinguish color, then because the absolute figure of rgb value is less, the scope of chromaticity coordinates value rgb is very little, and measured value has little fluctuation just to cause big error easily, easily makes software erroneous judgement occur; And the scope of tristimulus values RGB is bigger comparatively speaking, therefore as long as fluctuation is not very big less with regard to error.And chromaticity coordinates value rgb is not very sensitive to brightness; The color category that can describe is less, so as preferred, the utility model adopts tristimulus values RGB to come different colours is distinguished.
Draw by experiment, the measured value under different color blocks, the different operating condition and the variation tendency of ideal value are roughly the same, but a certain distance is numerically arranged.Therefore, based on the actual measured value in look source, divided the color gamut that is adapted to native system and look source:
The color coding rule list:
Native system will be assigned to ten kinds of common colors such as white, black, red, green, blue, yellow, pink, cyan, orange, gray to 512 color codes according to actual needs, discern this ten kinds of common colors by software.
Rgb value equals 444,555 or 554, and then color is white.
Rgb value equals 111,112,121,122,211,212,221,222,321,322 or 332, and then color is black.
Rgb value equals 311,312,411,412,422,511,512,513,521,522,523,533 or 531, and then color is red.
Rgb value equals 131,132,141,142,151,152,153,231,232,241,242,243,251,252,253,254,341,342,343,35,352,353,354,355,453 or 454, and then color is green.
Rgb value equals 113,114,115,123,124,125,135,214,215,223,224,225,335,345,445,245 or 145, and then color is blue.
Rgb value equals 331,441,442,443,551,552,553,431,541,451 or 452, and then color is yellow.
Rgb value equals 213,313,314,315,323,324,325,334,413,414,415,423,424,425,434,435,514,515,524,525,534,535 or 545, and then color is pink.
Rgb value equals 133,134,143,144,145,154,155,233,234,235,244,255 or 455, and then color is cyan.
Rgb value equals 421,532,542,543 or 432, and then color is orange.
Rgb value equals 433,544,344 or 333, and then color is gray.
As: R=105, G=30, B=200 is encoded to 314, then is judged as pink.
The foregoing description is to explanation of the present utility model, is not to qualification of the present utility model, and any structure after simple transformation on the utility model basis all belongs to protection domain of the present utility model.
Claims (3)
1. colors automatic recognizing system, it is characterized in that: comprise adopting look device (1), RGB acquisition module (2), color identification module (3) and exporting display module (4) of connecting successively, described look device (1) the output chrominance signal of adopting is given RGB acquisition module (2), RGB acquisition module (2) is exported to color identification module (3) with the color numerical value that obtains, and color identification module (3) is exported to output display module (4) with the color that identifies and shown.
2. a kind of colors automatic recognizing system as claimed in claim 1, it is characterized in that: the described look device (1) of adopting comprises camera bellows (11), camera assembly (12) and collection hole (13), look source, described camera assembly (12) is arranged in the camera bellows (11), and the look source is gathered hole (13) and is arranged on the face of camera bellows (11).
3. a kind of colors automatic recognizing system as claimed in claim 2, it is characterized in that: described camera assembly (12) comprises camera (121), removable flat board (122), support (123) and output line (124), described camera (121) is placed on the removable flat board (122), support (123) be supported on removable flat board (122) below, the output terminal of camera (121) is connected with output line (124), and described output line (124) transfers data to RGB acquisition module (2).
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CNU2006201062773U CN201028984Y (en) | 2006-08-01 | 2006-08-01 | Automatic color recognition system |
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CNU2006201062773U CN201028984Y (en) | 2006-08-01 | 2006-08-01 | Automatic color recognition system |
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Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102096822A (en) * | 2010-12-24 | 2011-06-15 | 华为终端有限公司 | Color discrimination method and device |
CN102324100A (en) * | 2011-09-30 | 2012-01-18 | 优视科技有限公司 | Real-time color acquiring method and device based on camera of mobile terminal |
CN103115682A (en) * | 2013-01-15 | 2013-05-22 | 北京林业大学 | Device capable of identifying color automatically |
CN103971110A (en) * | 2013-01-30 | 2014-08-06 | 富港电子(东莞)有限公司 | Method for capturing color of physical object |
CN112180526A (en) * | 2020-10-04 | 2021-01-05 | 常熟高通智能装备有限公司 | Intelligent manufacturing method of layer-stranded communication optical cable core |
CN113490874A (en) * | 2020-10-04 | 2021-10-08 | 常熟高通智能装备有限公司 | Intelligent manufacturing method of layer-stranded communication optical cable core |
-
2006
- 2006-08-01 CN CNU2006201062773U patent/CN201028984Y/en not_active Expired - Fee Related
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102096822A (en) * | 2010-12-24 | 2011-06-15 | 华为终端有限公司 | Color discrimination method and device |
CN102324100A (en) * | 2011-09-30 | 2012-01-18 | 优视科技有限公司 | Real-time color acquiring method and device based on camera of mobile terminal |
CN103115682A (en) * | 2013-01-15 | 2013-05-22 | 北京林业大学 | Device capable of identifying color automatically |
CN103115682B (en) * | 2013-01-15 | 2015-03-11 | 北京林业大学 | Device capable of identifying color automatically |
CN103971110A (en) * | 2013-01-30 | 2014-08-06 | 富港电子(东莞)有限公司 | Method for capturing color of physical object |
CN112180526A (en) * | 2020-10-04 | 2021-01-05 | 常熟高通智能装备有限公司 | Intelligent manufacturing method of layer-stranded communication optical cable core |
CN113490874A (en) * | 2020-10-04 | 2021-10-08 | 常熟高通智能装备有限公司 | Intelligent manufacturing method of layer-stranded communication optical cable core |
CN112180526B (en) * | 2020-10-04 | 2021-12-24 | 江苏科信光电科技有限公司 | Intelligent manufacturing method of layer-stranded communication optical cable core |
CN113490874B (en) * | 2020-10-04 | 2023-04-04 | 新疆亚鑫达线缆制造有限公司 | Intelligent manufacturing method of layer-stranded communication optical cable core |
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