摘要：Texture analysis and classification are some of the problems which have been paid much attention by image processing scientists since late 80s. If texture classification 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 make their performance biased on popular databases. In this paper, some metrics are proposed to collect more actual database of texture images. The proposed approach is included two stages. The first one is developing feature representation based on structural and statistical features and the next one is consisted an algorithm which termed SFCO to collect images based on metrics. Finally, in order to prove the quality of developed metrics, some texture classification approaches are applied on proposed database. Decreasing the probability of biasing texture classification approaches on popular database is the main advantage of this paper
关键词：Database Collecting; Texture Classification; Statistical Features; Structural Features
