Breast cancer is the most common form of cancer of women. According to statistics, one out of every eight women will develop breast cancer in her lifetime. Thanks to recent advances in medicine, there are more and more effective methods in the treatment of breast cancer. Since the cause of breast cancer is unknown, early detection is very important. If detected early, the fiveyear survival rate...

T exture analysis is the extraction of textural features from images (Tuceryan and Jain, 1998). The meaning of texture varies, depending on the area of science in which it is used. In general, texture refers to the physical character of an object or the appearance of an image. In image analysis, texture is defined as a function of the spatial variation in intensities of pixels (Tuceryan and Jai...

Introduction: To explore diagnostic potential of computerize texture analysis methods in discrimination of the normal, benign and malignant ovarian lesions by CT scan imaging.   Materials and Methods: Ovarian CT image database consists of 10 normal, 10 benign and 3 malignant which were reported by radiologist and proven by clinical examinat...

Computer-based texture analysis (TA) is used to characterize the spatial distribution of signal intensity variations within local regions (2D or 3D) in an image, and can enable us to detect signal signatures and biology-related information that are otherwise imperceptible to the human eye. Although visual texture1 is not a completely well-defined concept, image texture can be captured quantitat...

Color induced texture analysis is explored, using two texture analysis techniques: the co-occurrence matrix and the color correlogram as well as color histograms. Several quantization schemes for six color spaces and the humanbased 11 color quantization scheme have been applied. The VisTex texture database was used as test bed. A new color induced texture analysis approach is introduced: the pa...

This chapter presents a novel and generic framework for image segmentation using a compound image descriptor that encompasses both colour and texture information in an adaptive fashion. The developed image segmentation method extracts the texture information using low-level image descriptors (such as the Local Binary Patterns (LBP)) and colour information by using colour space partitioning. The...

The analysis of texture in images is an important area of study. Image benchmarks such as Meastex and Vistex have been developed for researchers to compare their experiments on these texture benchmarks. In this paper we compare five different texture analysis methods on these benchmarks in terms of their recognition ability. Since these benchmarks are limited in terms of their content, we have ...

In this paper we propose a technique for classifying images by modeling features extracted at di erent scales. Speci cally, we use texture measures derived from Pap smear cell nuclei images using a Grey Level Co-occurrence Matrix (GLCM). For a texture feature extracted from the GLCM at a number of distances we hypothesise that by modeling the feature as a continuous function of scale we can obt...

in this study, ultrafiltrated feta cheese was prepared from cow’s milk ultrafiltraton retentate and soymilk blend. rennet and calcium chloride were used simultaneously as coagulant to coagulate cow’s milk proteins and soymilk proteins, respectively. then, the effect of storage period on physical (texture profile analysis test, penetration test), chemical (total solids, protein, fat) and sensory...