Homomorphic filtering based image processing method and system

Abstract

The invention provides a homomorphic filtering based image processing method and system. The method includes the steps of acquiring an original code map; subjecting the original code map to homomorphic filtering to obtain a code map subjected to homomorphic filtering; based on a preset partitioning algorithm, partitioning the code map subjected to homomorphic filtering into a plurality of code map sub-units; subjecting each code map sub-unit to binarization by an OTSU algorithm to obtain a binary code map sub-unit; combining the binary code map sub-units to generate a final binary code map. The homomorphic filtering based image processing method and system has the advantages that before binarization of the code map, homomorphic filtering is performed first, the images are effectively enhanced by homomorphic filtering, image quality decline caused by insufficiency of light is effectively avoided, the advantages of the OTSU algorithm are given to maximum play, a foreground and a background are precisely distinguished, no effective information is lost from the binary images, image binarization quality is improved, and the following image processing is simplified.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to an image processing method and system based on homomorphic filtering. Background technique [0002] In the field of digital image processing, image binarization occupies a very important position, especially in practical image processing, there are a large number of systems that are realized by binary image processing, for example, electronic eye scanning license plate, mobile phone camera shooting One-dimensional code or two-dimensional code, etc. [0003] The principle of image binarization is: first process the image into a grayscale image, and then take an appropriate threshold, all pixels whose grayscale is greater than or equal to the threshold are judged to belong to a specific object, and their grayscale value is 255, otherwise, Pixels whose grayscale is lower than the threshold are excluded from the object area, and the grayscale value is 0, indicat...

AI Technical Summary

Problems solved by technology

[0005] Although the OTSU algorithm is the best algorithm for threshold selection in image segmentation, however, in the process of recognizing the two-dimensional code map, since the code points on the code map are very small, and the color difference between the code map background and the code point color is small, Or the image quality is degraded due to insufficient light. Therefore, when directly using the OTSU binarization algorithm to binarize the two-dimensional code map, some code points will be mistaken for the background and filtered out, so that the binarized code map Part of the effective information is lost, which will affect the subsequent code pattern recognition

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