A New Sequential Skeletonization Algorithm for 2-D Gray Images in Computer Vision Applications

The article describes the application of the Hough transform to a honeycomb block image. The problem of cutting a mold from a honeycomb block is described. A number of image transformations are considered to increase the efficiency of the Hough algorithm. A method for obtaining a binary image using a simple threshold, a method for obtaining a binary image using Otsu binarization, and the Canny Edge Detection algorithm are considered. The method of binary skeleton (skeletonization) is considered, in which the skeleton is obtained using 2 main morphological operations: Dilation and Erosion. As a result of a number of experiments, the optimal sequence of processing the original image was revealed, which allows obtaining the coordinates of the maximum number of faces. This result allows one to choose the optimal places for cutting a honeycomb block, which will improve the quality of the resulting shapes.

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A New Sequential Skeletonization Algorithm for 2-D Gray Images in Computer Vision Applications

Cited by 2 publications

References 11 publications

Hardware implementation of digital image skeletonization algorithm using FPGA for computer vision applications

Hardware implementation of digital image skeletonization algorithm using FPGA for computer vision applications

Application of sequential processing of computer vision methods for solving the problem of detecting the edges of a honeycomb block

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