An Adaptive Binarization Method Based on Deblocking PCNN

In recent years, the pulse coupled neural network (PCNN) is widely used in image segmentation, but the existing algorithm has an unsatisfactory performance with the definition of single threshold, especially in uneven illumination or low contrast image. In this paper, in order to eliminate the impac...

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Bibliographic Details
Published in淡江理工學刊 Vol. 20; no. 4; pp. 503 - 510
Main Authors Liejun Wang, Song Zhang, Yanqing Qi
Format Journal Article
LanguageEnglish
Published 淡江大學 01.01.2017
Subjects
OSTU
PCNN
Image Segmentation
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Summary:In recent years, the pulse coupled neural network (PCNN) is widely used in image segmentation, but the existing algorithm has an unsatisfactory performance with the definition of single threshold, especially in uneven illumination or low contrast image. In this paper, in order to eliminate the impact of the illumination and improve the adaptability, deblocking PCNN algorithm is utilized. It segments the image into several rectangles with the same size. Then PCNN algorithm is applied to segment each block and stopped by improved OSTU. The emulation experiment shows that this method is better than traditional image segmentation method in uneven illumination or low contrast image.
ISSN:2708-9967
DOI:10.6180/jase.2017.20.4.12