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Intelligent electric meter chip image binarization processing method based on adaptive mixed threshold

An image binarization, smart meter technology, applied in image data processing, image enhancement, image analysis and other directions, can solve the problems of binarization, uneven image brightness, inability to achieve rapid processing and improve efficiency.

Pending Publication Date: 2020-11-24
STATE GRID NINGXIA ELECTRIC POWER CO LTD MARKETING SERVICE CENT STATE GRID NINGXIA ELECTRIC POWER CO LTD METERING CENT
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the disadvantages of the prior art that the chip image cannot be effectively binarized when a single global or local threshold algorithm is used due to the influence of uneven illumination and different character sizes of the chip image, and provides a method based on The image binarization processing method of smart meter chip with adaptive mixed threshold, aiming at the problem of uneven brightness of smart meter chip image, improves the traditional local threshold method, and adds the global threshold and local threshold to solve the problem of local threshold. The algorithm does not consider the overall effect of the image; for the problem of different character sizes in the chip image, the window width is automatically calculated for each pixel by stroke width conversion, and the local threshold is calculated according to different window widths and adaptive parameters, so as to adaptively Calculate the mixed threshold, avoid manual adjustment of parameters, and improve the efficiency of the algorithm

Method used

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  • Intelligent electric meter chip image binarization processing method based on adaptive mixed threshold
  • Intelligent electric meter chip image binarization processing method based on adaptive mixed threshold
  • Intelligent electric meter chip image binarization processing method based on adaptive mixed threshold

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Embodiment 1

[0055] This embodiment includes steps: S1, acquiring the original image, and preprocessing the original image to obtain a grayscale image; S2, calculating the global threshold T according to the grayscale value of the entire grayscale image g ; S3. Calculate the stroke width corresponding to each pixel in the grayscale image, and adaptively calculate the window width corresponding to each pixel, and calculate the local threshold T of each pixel according to the pixel value in each window w ; S4, the global threshold T g and a local threshold T w Combining calculations to obtain a blending threshold T; S5, performing a binarization operation on the grayscale image according to the blending threshold T to obtain a binarized image.

[0056] Preferably, the preprocessing of the original image in S1 includes: S1.1, performing median filtering on the original image, and the preferred specific method for performing median filtering on the original image in S1.1 is: S1.1.1, first usi...

Embodiment 2

[0059] Such as figure 1 As shown, the present embodiment also includes on the basis of Embodiment 1: S2 is specifically: set the grayscale image f(x, y) to have N pixels and L gray levels; divide f(x, y) into for C 0 and C 1 Two categories, C 0 class by f(x,y) in grayscale [0,T g ] in the composition of pixels, C 1 class by f(x,y) in grayscale [T g+1, L] in the pixel points, the variance between the two classes is: σ 2 =μ 0 (m 0 -m) 2 +μ 1 (m 1 -m) 2 , where μ 0 and μ 1 respectively C 0 and C 1 Probability of two classes, m 0 and m 1 respectively C 0 and C 1 The gray mean value of the two classes, m is the gray mean value of the entire gray scale image; in the L-level gray scale range, the threshold corresponding to the maximum variance between classes is selected by traversal method, which is the global threshold T g . S3 includes steps: S3.1, calculate the stroke width corresponding to each pixel, and adaptively calculate the window width corresponding t...

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Abstract

The invention discloses an intelligent electric meter chip image binarization processing method based on an adaptive mixed threshold. The method comprises the following steps: S1, preprocessing an original image to obtain a grayscale image; s2, calculating a global threshold Tg according to the gray value of the whole gray image; s3, calculating a stroke width corresponding to each pixel point inthe grayscale image, adaptively calculating a window width corresponding to each pixel, and calculating a local threshold Tw of each pixel according to a pixel value in each window; s4, combining theglobal threshold Tg and the local threshold Tw to calculate a mixed threshold T; and S5, performing binarization operation on the grayscale image according to the mixed threshold T to obtain a binarized image. Compared with the prior art, the processing method provided by the invention improves the traditional local threshold method for the problem of non-uniform brightness of the chip image of the intelligent electric meter, and performs weighted addition on the global threshold and the local threshold, thereby solving the problem that the local threshold algorithm does not consider the overall effect of the image.

Description

technical field [0001] The invention relates to image processing of a smart meter chip, in particular to a binarization processing method for an image of a smart meter chip based on an adaptive mixed threshold. Background technique [0002] The smart meter is an important basic equipment in the smart grid. During its storage, transportation and installation, problems such as mixed use and misuse of chips may occur. Therefore, it is necessary to detect the chip type of the smart meter. Optical character recognition (OCR) is a commonly used image character recognition technology, and binarization is one of the most important steps of this technology. Due to the influence of many environmental factors such as complex background, shooting angle and light intensity, the captured chip image will have problems such as uneven brightness and different sizes of some characters, which makes the binarization effect unsatisfactory, which in turn affects the subsequent character recogniti...

Claims

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Application Information

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IPC IPC(8): G06T7/136G06T7/90G06T7/62G06T7/13G06T7/00G06F17/14
CPCG06T7/136G06T7/90G06T7/62G06T7/13G06T7/0004G06F17/14G06T2207/20032
Inventor 田瑞刘朋远窦圣霞丁海丽严绍奎张洁周媛奉马晓昉张翔张胜强
Owner STATE GRID NINGXIA ELECTRIC POWER CO LTD MARKETING SERVICE CENT STATE GRID NINGXIA ELECTRIC POWER CO LTD METERING CENT
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