Fuzzy morphology based feature identification in image processing

Abstract

Image processing has very important application in the national economy and the people's livelihood, but there exists many problems in the process for original image identification processing, such as edge unclear. In order to remove edge discontinuousness, forge edge and over-segmentation, the paper proposed an algorithm of fuzzy morphology based feature identification in image processing. The method is based on structure element of fuzzy mathematical morphology to identify feature, analyzed elements correlation, decided subjection function after pre-process images, ascertained best segmentation threshold adopting technology of auto-recognition best threshold. Then the algorithm took best threshold and path cost function as constraint condition to reduce search scope, enhance algorithm execute speed. Finally it extracted edge and identified image geometry features by dint of watershed algorithm. The paper took packaged granary grain quantity intelligent reckoning for example to make digital emulation, and the results showed that it not only can make image edge continuous, but also can remove the phenomena of forge edge and over-segmentation, and the image changes smoother and more flexible by using the algorithm to process images. © 2010 Springer-Verlag Berlin Heidelberg.