Quick rectangle detection method of images high resolution and high order of magnitude

Abstract

The invention relates to a quick rectangle detection method of images with high resolution and high order of magnitude. The method comprises the following steps: firstly, pretreating each boundary pixel point set to obtain a cross point set taking a boundary pixel as a center; using a PPHT (progressive probabilistic Hough transform) algorithm and comparing with surrounding Hough parameters to obtain a straight line; and finally searching towards two sides of the straight line and deleting the whole cross point set to which the boundary pixels on the straight line belong. The process is circulated until a small quantity of pixels residues. On the basis of the extracted straight line, the established rectangle rule in which a pair of accurately matched parallel lines are detected firstly and then right-angle sides not completely matched are detected is utilized to detect the rectangles in the images. The method has good robustness for interferences caused by false boundaries and lens distortion due to dusts of a background area and is not limited by the different rectangle sizes; and thus a reliable rectangle detection method is applied for modernized industrial production of large-size rectangle boards.

Description

technical field [0001] The invention relates to a machine vision and image processing technology, in particular to a fast rectangle detection method for high-resolution and large-order images. Background technique [0002] Rectangle detection has a wide range of applications in the field of computer vision, such as the detection of buildings in remote sensing images, the detection of license plates, and so on. In actual industrial production, the assembly line operation of oversized glass requires us to accurately detect the position of rectangular glass. The factory uses a high-resolution scanning camera to obtain the two-dimensional coordinates of the boundary points of glass and other plates. A real-time and accurate rectangle detection algorithm is needed to detect the rectangle position in the pixel coordinates to facilitate the subsequent production process. Usually, due to factors such as dust in the background area, many wrong boundaries of the background are extrac...

AI Technical Summary

Problems solved by technology

The images in these fields are all dense matrices with normal resolution. When applying these algorithms to the detection of large-size rectangular plates (such as glass) in actual industrial production that we want to study, in the face of high-resolution large-scale sparseness Matrix, the detection effect and efficiency of the algorithm will be very poor

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