The statistical approaches such as texture spectrum and local binary pattern methods have been discussed in this paper. The features are extracted by the computation of LBP and Texture Spectrum histogram. A combined approach of LBP with texture spectrum is also proposed further. Experiments of texture feature extraction, classification of textures and similarity-based image-to-image matching ar...

facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. in recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. as machine vision and artificial intelligence advan...

This paper presents a novel method for interest region description. We adopted the idea that the appearance of an interest region can be well characterized by the distribution of its local features. The most well-known descriptor built on this idea is the SIFT descriptor that uses gradient as the local feature. Thus far, existing texture features are not widely utilized in the context of region...

The image space, scale and orientation domains can give valuable clues not seen in either individual of the domains. First we decomposed the face image into different orientation and scale by Gabor filter. Second, we combine local binary pattern analysis with Gabor. It gives a good face representation for recognition. Then we classify in discriminant based up on median histogram distance. The f...

In this paper, an efficient local operator, namely the Local Quantization Code (LQC), is proposed for texture classification. The conventional local binary pattern can be regarded as a special local quantization method with two levels, 0 and 1. Some variants of the LBP demonstrate that increasing the local quantization level can enhance the local discriminative capability. Hence, we present a s...

In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

This paper presents an approach to derive critical points of a shape, the basis of a Reeb graph, using a combination of a medial axis skeleton and features along this skeleton. A Reeb graph captures the topology of a shape. The nodes in the graph represent critical points (positions of change in the topology), while edges represent topological persistence. We present an approach to compute such...

In this paper LBP and CM methods have been efficiently used for image retrieval for the content based image retrieval (CBIR) system. As LBP method may be sensible to noise in case of comparing neighboring pixels. The drawback of CM is it may be inefficient with too much details image. So it will be better to combine the feature of both method and utilized the property of both the two methods. I...

An effective remote sensing image scene classification approach using patch-based multi-scale completed local binary pattern (MS-CLBP) features and a Fisher vector (FV) is proposed. The approach extracts a set of local patch descriptors by partitioning an image and its multi-scale versions into dense patches and using the CLBP descriptor to characterize local rotation invariant texture informat...

This paper presents a novel method for hierarchically organizing large face databases, with application to efficient identity-based face retrieval. The method relies on metric learning with local binary pattern (LBP) features. On one hand, LBP features have proved to be highly resilient to various appearance changes due to illumination and contrast variations while being extremely efficient to ...