STI Dataset Link
Texture analysis plays an important role in many image processing applications to describe the image content or objects. On the other hand, visual surface defect detection is a highly research field in the computer vision. Surface defect refers to abnormalities in the texture of the surface. So, in this link a dual purpose benchmark dataset is proposed for texture image analysis and surface defect detection titled stone texture image (STI dataset). The proposed benchmark dataset consist of 4 different class of stone texture images. The proposed benchmark dataset have some unique properties to make it very near to real applications. Dual purpose is the main advantage of the STI dataset Local rotation in captured images Different zoom rates in captured images Local and global repetitive textures, because of natural features of stone kinds. Low-size and high-size repetitive textures jointly Different textures with same human visual scene Low-size and high-size defects Different kinds of abnormalities in color, texture and shape.