Innovative Texture Database Collecting Approach and Feature Extraction Method based on Combination of Gray Tone Difference Matrixes, Local Binary Patterns, and K-means Clustering

  • سال انتشار: 1393
  • محل انتشار: اولین کنفرانس ملی کامپیوتر، فن آوری اطلاعات و ارتباطات
  • کد COI اختصاصی: CCITC01_052
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 915
دانلود فایل این مقاله

نویسندگان

Shervan Fekri-Ershad

Department of Computer Science and Engineering Shiraz University Shiraz, Fars, Iran

چکیده

Texture analysis and classification are some of the problems which have been paid much attention by image processing scientists since late 80s. If texture analysis is done accurately, it can be used in many cases such as object tracking, visual pattern recognition, and face recognition. Since now, so many methods are offered to solve this problem. Against their technical differences, all of them used same popular databases to evaluate their performance such as Brodatz or Outex, which may be made their performance biased on these databases. In this paper, an approach is proposed to collect more efficient databases of texture images. The proposed approach is included two stages. The first one is developing feature representation based on gray tone difference matrixes and local binary patterns features and the next one is consisted an innovative algorithm which is based on K-means clustering to collect images based on evaluated features. In order to evaluate the performance of the proposed approach, a texture database is collected and fisher rate is computed for collected one and well known databases. Also, texture classification is evaluated based on offered feature extraction and the accuracy is compared by some state of the art texture classification methods.

کلیدواژه ها

Database Collecting, Texture Classification, Local Binary Patterns, Texture analysis, Gray Tone Difference Matrixes, K-means Clustering

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.