Adaptive threshold value color image edge detection method based on FPGA (Field Programmable Gate Array) and Kirsch

An adaptive threshold, edge detection technology, applied in image enhancement, image analysis, image data processing and other directions, to achieve the effect of improved effect, easy implementation and strong flexibility

Inactive Publication Date: 2017-09-15
SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0005] In order to solve the technical problems existing in the prior art, the present invention provides a kind of adaptive threshold color image edge detection method based on FPGA and Kirsch, uses Kirsch operator as the benchmark of edge detection, realizes the adaptive threshold color image by means of FPGA platform Edge det

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  • Adaptive threshold value color image edge detection method based on FPGA (Field Programmable Gate Array) and Kirsch
  • Adaptive threshold value color image edge detection method based on FPGA (Field Programmable Gate Array) and Kirsch
  • Adaptive threshold value color image edge detection method based on FPGA (Field Programmable Gate Array) and Kirsch

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[0031] Example

[0032] The present invention uses FPGA as the core of timing control and data processing, and uses OV7725 as the source of image data collection. Such as figure 1 Shown is the flow chart of the present invention, which is mainly divided into six steps, including image color decomposition, image filtering and denoising, calculating threshold and Kirsch gradient value, realizing image morphology processing, synthesizing RGB888 format data, designing VGA circuit and displaying result. In the following, a color image with flowers as the target object is used as a preferred embodiment to introduce the implementation process of the present invention in detail. Such as figure 2 As shown, the color image includes two objects of different colors, the subject to be detected is a red flower, and the background is covered by green branches and leaves, and the two have areas that overlap and reflect each other. This embodiment uses the method of the present invention to p...

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Abstract

The invention relates to an adaptive threshold value color image edge detection method based on an FPGA (Field Programmable Gate Array) and Kirsch. The method comprises the following steps that: firstly, converting collected image data into YCbCr, and carrying out Gaussian filtering and median filtering processing on a Y component in the YCbCr; and then, carrying out edge detection, carrying out morphological processing on an image subjected to the edge detection, synthetizing Y'Cb'Cr', and converting the Y'Cb'Cr' into an RGB888 format to be displayed in virtue of a VGA (Video Graphics Array). A Kirsch operator is taken as the reference of the edge detection, the edge detection of the adaptive threshold value color image is realized in virtue of the FPGA platform, and in addition, visual display is carried out through the VGA in the RGB8888 format so as to improve a color image edge detection effect. By use of the method, the defects in the prior art that image processing instantaneity is insufficient can be made up, and the edge detection is more flexible so as to be favorable for improving the accuracy of object edge detection.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to an adaptive threshold color image edge detection method based on FPGA and Kirsch. Background technique [0002] The edge of an object is an important basis to reflect its characteristics, and the edge detection of digital images is the premise of many image processing technologies such as image restoration, image enhancement, region segmentation, and feature extraction. For a long time, scholars at home and abroad have been very active in the research of edge detection technology, so there have been a variety of edge detection algorithms. There are many classic edge detection algorithms commonly used, such as Sobel operator, Laplace operator, Robert operator, Canny operator, etc. The threshold selection of these traditional algorithms is very important, but most of them are fixed thresholds set in advance, the flexibility is limited, and these algorithms ignore ...

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Application Information

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IPC IPC(8): G06T7/13G06T7/136
CPCG06T7/13G06T7/136G06T2207/10024G06T2207/20032
Inventor 徐紫洋马国欣
Owner SOUTH CHINA UNIV OF TECH
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