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Texture Classification in Sparse and Irregularly Sampled Data

عنوان مقاله: Texture Classification in Sparse and Irregularly Sampled Data
شناسه ملی مقاله: ICMVIP02_091
منتشر شده در دومین کنفرانس ماشین بینایی و پردازش تصویر در سال 1381
مشخصات نویسندگان مقاله:

M Petrou - School of Electronics and Physical Sciences University of Surrey, Guildford GU۲ ۷XH, United Kingdom
A Talepbour

خلاصه مقاله:
The Trace transform is a generalisation of the Radon transform that allows one to construct image features that do not necessarily have meaning in terms of human perception, but they measure different image characteristics. The ability of producing thousands of features from an image allows one to be selective as to which are appropriate for a particular task. In this paper we propose the use of such an approach to the problem of texture classification with irregularly sampled data and compare its results with the case of regularly sampled data.

کلمات کلیدی:
Texture Recognition, Trace transform, Irregularly sampled data, Hough transform

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/125726/