This paper describes a texture based shape connection method for reconstructing parts of an object shape into its entire 3-D shape. This method employs a stereo camera to obtain the parts of an object. First, this method finds overlaps between the parts, obtained from a number of different viewpoints, using texture. Then, the method uses the results for estimating the relative position-and-orie...

Modelling the appearance of 3D objects undergoing large pose variation relies on recovering correspondence of both shape and texture across views. The problem is hard because changes in pose not only introduce self-occlusions hence inconsistent 2D features between views, but also cause non-linear variations in both the shape and texture of object appearance. In this paper, we present an approac...

Image segmentation plays a major role in the analysis of medical image disease diagnosis. Image features extracted is the basis for precise image segmentation. Variable nature of image features, such as size, shape, intensity, color, texture etc., cause complexity in the image segmentation and analysis of the image nature. Existing work estimate the effectiveness of the level-set shape beside w...

Texture-based computer-aided diagnosis (CADx) of microcalcification clusters is more robust than the state-of-art shape-based CADx because the performance of shape-based approach heavily depends on the effectiveness of microcalcification (MC) segmentation. This paper presents a texture-based CADx that consists of two stages. The first one characterizes MC clusters using texture features from gr...

Problem statement: Elastography is developed as a quantitative approach to imaging linear elastic properties of tissues to detect suspicious tumors. We propose an automatic feature extraction method in ultrasound elastography and echography for characterization of breast lesions. Approach: The proposed algorithm was tested on 40 pairs of biopsy proven ultrasound elastography and echography imag...

The computer vision strategies used to recognize a fruit rely on four basic features which characterize the object: intensity, color, shape and texture. This paper proposes an efficient fusion of color and texture features for fruit recognition. The recognition is done by the minimum distance classifier based upon the statistical and co-occurrence features derived from the Wavelet transformed s...

In RBIR, texture features are crucial in determining the class a region belongs to since they can overcome the limitations of color and shape features. Two robust approaches to model texture features are Gabor and curvelet features. Although both features are close to human visual perception, sufficient information needs to be extracted from their sub-bands for effective texture classification....

the quality evaluation of agricultural products is one of the key factors in promoting their quality. in this study, a method based on combined image processing technique and artificial neural network was presented. separation of touching almonds under different positions is a very important step in design of grading devices. in this study, an image processing algorithm based on extracting crit...