مشخصات پژوهش

عنوان	Weighted Constraint Feature Selection of Local Descriptor for Texture Image Classification
نوع پژوهش	مقاله چاپ‌شده
کلیدواژه‌ها	Local binary pattern, weighted constraint feature selection, texture image classification.
چکیده	There are several statistical descriptors for feature extraction from texture images. Local binary pattern is one of the most popular descriptors for revealing the underlying structure of a texture. Recently several variants of local binary descriptors have been proposed. The completed local binary pattern is an efficient version that can provide discriminant features and consequently provide a high classification rate. It finely characterizes a texture by fusing three histograms of features.
پژوهشگران	رضا بوستانی (نفر پنجم)، محمد حسین شکور (نفر چهارم)، عدیل حسین محمد (نفر سوم)، فرهان الانزی (نفر دوم)، انتصار سعید جمای (نفر اول)