Title :
Texture classification using n-tuple pattern recognition
Author :
Hepplewhite, L. ; Stonham, T.J.
Author_Institution :
Dept. of Electr. Eng. & Electron., Brunel Univ., Uxbridge, UK
Abstract :
This paper presents a novel approach to real-time texture classification, derived from the n-tuple method of Bledsoe and Browning, for use in industrial applications. In recent years, various approaches have been presented for the texture classification problem. However, few have the computational tractability needed in an automated environment. In this paper, methods for texture classification based on approximations to the nth order co-occurrence spectrum are discussed. Limitations of these methods are highlighted before a new method based around Marr´s zero crossing sketch is presented. Preliminary results are presented comparing the new method and other n-tuple based schemes
Keywords :
computer vision; edge detection; image classification; image texture; real-time systems; Marr zero crossing sketch; approximations; binary texture cooccurrence spectrum; edge detection; n-tuple pattern recognition; real-time systems; texture classification; Computational efficiency; Data mining; Image processing; Inspection; Pattern recognition; Pixel;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.547253