Locally Adaptive Enhancement, Binarization, And Segmentation Of Images For Machine Vision
A. F. Lehar, Robert A. Gonsalves · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1984
This paper describes a flexible gray scale image enhancement scheme coupled with segmentation algorithms to automatically describe elemental shapes arising in a wide variety of images of interest in machine vision applications. The enhancement algorithm is a locally adaptive Fourier filter configured so as to easily perform either contrast enhancement or additionally apply more complex Fourier filters to enhance periodic features. The enhanced images are then presented to a thresholding and region filling algorithm which breaks the objects of interest into elemental shapes. These shapes are characterized by simple measures such as size, perimeter, and Euler number, and feature extraction tasks are built on the basis of these descriptors. The method has been applied to fingerprint classification, seismic data inspection, and automated handling of packages.