A method and system for image edge extraction based on structural constraint clustering

An image edge and structural constraint technology, applied in the field of image processing, can solve problems such as lack of edge detection accuracy, achieve strong universality, and eliminate noise interference

Active Publication Date: 2022-05-31
INST OF SOFTWARE - CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditionally implemented edge detection algorithms include canny operator, sobel operator, Prewitt operator, etc., as well as some edge detection methods based on deep learning, but none of them have sufficient edge detection accuracy.

Method used

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  • A method and system for image edge extraction based on structural constraint clustering
  • A method and system for image edge extraction based on structural constraint clustering
  • A method and system for image edge extraction based on structural constraint clustering

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Embodiment 1

[0055] The grayscale image Gray_img is represented by thresholding according to the adaptive threshold OTSU algorithm. First, statistical gray

[0058] The pixels of the thresholding map are represented by coordinates in order to convert the thresholding map into the input format of the subsequent steps.

[0059] Step S22: each pixel in the thresholding graph includes two components: pixel(i, j)={(i, j),

[0060] Each pixel after the coordinate representation contains two components, i, j is the coordinate information of the pixel, and grayscale is like

[0061] Step S23: construct a coordinate thresholding map P={pixel(1,1), pixel(1,2),  …pixel(i, j),  …

[0062] Among them, m is the number of pixels on the long side of P, and n is the number of pixels on the short side of P.

[0065] To the coordinate thresholding map P, all white bright spots are extracted according to the grayscale value grayscale, that is, grayscale=

[0066] The embodiment of the present invention utilizes t...

Embodiment 2

[0113] As shown in FIG. 15, an embodiment of the present invention provides an image edge extraction system based on structural constraint clustering,

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Abstract

The present invention relates to an image edge extraction method and system based on structural constraint clustering. The method includes: step S1: performing grayscale processing on the original image to obtain a grayscale image; thresholding the grayscale image to obtain the obtained Thresholding the graph; step S2: putting the thresholding graph into a planar Cartesian coordinate system to construct a coordinate thresholding graph; step S3: using the density clustering method to cluster the pixels in the coordinate thresholding graph into pixels Cluster; Step S4: For pixel clusters, perform cluster optimization under structural knowledge constraints to obtain edge clusters containing object edges; Step S5: Remove internal points contained in edge clusters for edge clusters, and obtain preliminary image edge extraction results; Step S6 : According to the preliminary image edge extraction results, use the edge correction based on graph search to get the final image edge extraction results. The method provided by the invention improves the automation degree of traditional edge detection and makes the extraction of object edges more efficient and accurate.

Description

A method and system for image edge extraction based on structural constraint clustering technical field The present invention relates to the field of image processing, be specifically related to a kind of image edge extraction method based on structural constraint clustering and system. Background technique Edge detection is a basic tool in graphics and image processing, computer vision and machine vision, usually used for Feature extraction and feature detection are designed to detect edges or discontinuous areas with obvious changes in a digital image. In one-dimensional space, a similar operation is called stride detection. An edge is the boundary line between different areas in an image, usually An edge image is a binary image. The purpose of edge detection is to capture areas with sharp changes in brightness, which Usually it's our focus. Two-degree discontinuities in an image are usually one of the following: Image depth discontinuities Continuations, im...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/13G06T7/136G06K9/62G06V10/762
CPCG06T7/13G06T7/136G06F18/23
Inventor 张常有薄文蔡晓峰武文佳田卓
Owner INST OF SOFTWARE - CHINESE ACAD OF SCI
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