Content Based Image Retrieval (CBIR) system using Inter Space Local Binary Patterns (ISLBP) based features with high retrieval rate and less computational complexity is proposed in this paper. The property of LBP is it extracts the information based on distribution of edges in an image. This property made it a powerful tool for feature extraction of images in the data base. First the image is s...

This paper discusses the concept of object’s shape identification using local binary pattern technique (LBP). Since LBP is computationally simple it has been utilized successfully for recognition of various objects. LBP which has the potential to be used in various identification related fields was applied on a number of different shaped objects, the process converted the given image in to 3x3...

An efficient texture modeling framework based on Topological Attribute Patterns (TAP) is presented considering topology related attributes calculated from Local Binary Patterns (LBP). Our main contribution is to introduce new efficient mapping mechanisms that improve some typical mappings for LBP-based operators in texture classification such as rotation invariant patterns ( ri ), rotation inva...

Face recognition is one of the most broadly researched subjects in pattern recognition. Feature extraction is a key step in face recognition. As an effective texture description operator, Local Binary Pattern (LBP) feature is firstly introduced by Ahonen et al into face recognition. Because of the advantages of simplicity and efficiency, LBP feature is widely applied and later on becomes one of...

This paper presents a new image indexing and retrieval algorithm by integrating color (HSV color histogram) and texture (directional binary wavelet patterns (DBWP)) features. For color feature, first the RGB image is converted to HSV image, and then histograms are constructed from HSV spaces. For texture feature, an 8-bit grayscale image is divided into eight binary bit-planes, and then binary ...

In this paper, we propose a novel representation, called Multiscale Block Local Binary Pattern (MB-LBP), and apply it to face recognition. The Local Binary Pattern (LBP) has been proved to be effective for image representation, but it is too local to be robust. InMB-LBP, the computation is done based on average values of block subregions, instead of individual pixels. In this way, MB-LBP code p...

-Texture classification is a major issue in image analysis and pattern recognition. A number of methods are proposed in the literature including Local Binary Pattern (LBP). The LBP variant (s) plays an active role to extract texture features for texture classification. These are rotation invariant, noise sensitive or noise insensitive mehods. Each method has its own advantages and disadvantages...

This paper presents a novel approach for texture classification and relevance with generalizing the well-known local binary patterns (LBP).

Local binary pattern (LBP) is an effective texture descriptor which has successful applications in texture classification and face recognition. Many extensions are made for conventional LBP descriptors. One of the extensions is dominant local binary patterns which aim at extracting the dominant local structures in texture images. The second extension is representing LBP descriptors in Gabor tra...

In this paper, inter space local binary pattern (ISLBP) algorithm for content based image retrieval (CBIR) is proposed. First the image is separated into red(R), green(G), and blue(B) color spaces, and these are used for inter space local binary patterns (ISLBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors by changing center pi...