We investigate the potential of mammographic parenchymal texture as a surrogate marker of the risk to develop Estrogen Receptor (ER) sub-type specific breast cancer. A case-control study was performed, including 118 cancer cases stratified by ER receptor status and 354 age-matched controls. Digital mammographic (DM) images were retrospectively collected and analyzed under HIPAA and IRB approval...

A detailed evaluation of the use of texture features in a query-by-example approach to image retrieval is presented. Three radically different texture feature types motivated by i) statistical, ii) psychological and iii) signal processing points of view are used. The features were evaluated and tuned on retrieval tasks from the Corel collection and then evaluated and tested on the TRECVID 2003 ...

This paper explores a design-based method to fuse Gabor filter features and co-occurrence probability features for improved texture recognition. The fused feature set utilizes both the Gabor filter’s capability of accurately capturing lower frequency texture information and the co-occurrence probability’s capability in texture information relevant to higher frequency components. Fisher linear d...

Texture features are important factor in content based image retrieval. Texture descriptors are important factor in grey scale images, but due to advancements in colour image processing textures descriptors are developed a major factor for colour space images. In this paper various colour and grey scale based texture features have been discussed that can be used for extraction of texture histog...

Texture features are widely used in image retrieval literature. However, conventional texture features are extracted from grayscale images without taking color information into consideration. We present two improved texture descriptors, named color Gabor wavelet texture (CGWT) and color Gabor opponent texture (CGOT), respectively, for the purpose of remote sensing image retrieval. The former co...

Texture is commonly used feature in most of the content-based image retrieval systems. This texture retrieval ability can be also applied to rock texture. The retrieval of the rock texture is a demanding task because of special character of rock. In this paper some existing contentbased image retrieval systems are tested with a sample set representing clearly different rock images. The recall a...

Texture Analysis plays an important role in the interpretation, understanding and recognition of terrain, biomedical or microscopic images. To achieve high accuracy in classification the present paper proposes a new method on textons. Each texture analysis method depends upon how the selected texture features characterizes image. Whenever a new texture feature is derived it is tested whether it...

Texture classification is an active topic in image processing which plays an important role in many applications such as image retrieval, inspection systems, face recognition, medical image processing, etc. There are many approaches extracting texture features in gray-level images such as local binary patterns, gray level co-occurence matrixes, statistical features, skeleton, scale invariant fe...

Image texture and color are important features for image segmentation. Several algorithms have been proposed using color features, texture features or combination of color and texture features for image segmentation in the literature. One of the important issues is how well these algorithms work on differentiating among different textures and colors. In this study, we analyze and compare some o...

Texture segmentation is the process of partitioning an image into regions with different textures containing similar group of pixels. Texture is an important spatial feature, useful for identifying object or region of interest. In texture analysis the foremost task is to extract texture features, which efficiently embody the information about the textural characteristics of the image. This can ...