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A method for visual detection of liquid crystal instrument pattern based on normalized zernike moment and grayscale matching

A grayscale matching, liquid crystal instrument technology, applied in instrumentation, image analysis, image data processing, etc., can solve the problems of high false detection rate, poor flexibility, errors, etc., to achieve less redundant information, strong image description ability, excellent Detect the effect of recognition ability

Active Publication Date: 2017-01-11
宁波智能装备研究院有限公司
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  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to solve the problems of high false detection rate, poor flexibility and the rotation and scaling of the image caused by the mechanical clamping error of the detected instrument in the actual detection environment in the problems existing in the gray scale matching of the image, and proposes a Visual detection method of liquid crystal instrument pattern based on normalized Zernike moments and grayscale matching

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  • A method for visual detection of liquid crystal instrument pattern based on normalized zernike moment and grayscale matching
  • A method for visual detection of liquid crystal instrument pattern based on normalized zernike moment and grayscale matching
  • A method for visual detection of liquid crystal instrument pattern based on normalized zernike moment and grayscale matching

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specific Embodiment approach 1

[0033] Specific embodiment one: a kind of liquid crystal meter pattern visual detection method based on normalized Zernike moments and grayscale matching of the present embodiment is specifically prepared according to the following steps:

[0034] Step 1. Collect the overall image to be detected from the camera such as figure 2 , set the pattern to be detected according to the overall image information to be detected, set the ROI of the image, intercept the sub-image of the detected area, and gray-scale the sub-image as the image to be detected (src_GrayImage); read from the database The corresponding template image (templ_GrayImage);

[0035] Step 2. Fill the image to be detected and the template image into a square image (the Zernike moment requires the image to be a square image), and translate the center of gravity of the detection image and the template image to the center of the square image, and perform translation normalization to generate a translation image to be de...

specific Embodiment approach 2

[0049] Specific embodiment two: the difference between this embodiment and specific embodiment one is: in step 2, the image to be detected and the template image are filled into a square image (the Zernike moment requires the image to be a square image), and the center of gravity of the detection image and the template image The specific process of translating to the center of the square image and performing translation normalization to generate a translation to-be-detected image and a translation template image is as follows:

[0050] (1) Determine whether the width and height of each image are equal, if not, square the image: compare the width and height of each image, select the larger width and height as the side length of the square image, and ensure The length of the side length is an odd number, construct a square image, and set the pixels of the square image to 0, that is, the square image is black; according to the size of the image, add some pixels to the side length ...

specific Embodiment approach 3

[0052] Specific embodiment three: the difference between this embodiment and specific embodiment one or two is: adopt Mukundan fast algorithm to calculate the Zernike moments of image to be checked and template image in step 3. The specific process is:

[0053] (1) Use "square-circle transformation" to transform the square image g(x,y) into polar coordinates f(r,ξ), r,ξ are obtained by the following formula: γ=max{|x|,|y |}, if |x|=γ, then If |y|=γ, then The normalized polar coordinates corresponding to the pixel (r, ξ) are: r=2γ / N, θ=πξ / 4γ, where N is the number of side length pixels of the square image;

[0054] (2) Calculation of Zernike radial n-order m-order polynomial R by iterative method nm (r); Where m≥0 and n-k is an even number, B nmk = ( - 1 ) ( n - ...

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Abstract

The invention relates to liquid crystal meter pattern visual detection methods, and provides a liquid crystal meter pattern visual detection method based on normalization Zernike moment and gray matching. The method aims to solve the problems that image error detection rate is high, flexibility is poor, and images are rotated and zoomed. The method includes the implementation steps that 1, an image to be detected and a template image are obtained; 2, a horizontal moving image to be detected and a horizontal moving template image are generated; 3, the Zernike moment of the horizontal moving image to be detected and the Zernike moment of the horizontal moving template image are calculated; 4, a scale normalization moment Znm is generated; 5, a moment vector Zsrc and a moment vector Ztem are established; 6, a determining feature vector J is established; 7, the degree of gray matching is obtained; 8, an updated determining feature vector J' is obtained; 9, the percent of similarity is obtained; 10, a detection result is obtained. The method is applied to the field of visual detection on liquid crystal meter patterns.

Description

technical field [0001] The invention relates to a liquid crystal instrument pattern visual detection method based on normalized Zernike moment and gray scale matching. Background technique [0002] With the wide application of liquid crystal instruments and large-scale automatic production, quality inspection before leaving the factory has become a key production link. The key point of quality inspection is the pattern detection of the LCD screen of the instrument, that is, under a given input signal, it is checked whether the pattern information displayed on the LCD screen is correct. The LCD instrument pattern detection based on machine vision can largely replace the traditional manual detection, which requires a general, efficient and accurate detection method for the characteristics of the LCD screen pattern and the visual detection system. [0003] At present, the pattern detection of liquid crystal instruments mostly adopts the template matching method based on graysc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06K9/00
Inventor 于金泳张焯然高会军
Owner 宁波智能装备研究院有限公司
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