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
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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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