In this paper we present an approach to music genre classification which converts an audio signal into spectrograms and extracts texture features from these time-frequency images which are then used for modeling music genres in a classification system. The texture features are based on Local Binary Pattern, a structural texture operator that has been successful in recent image classification re...

Breast cancer is a frequent cancer diseases and it is the leading cause of cancer death among women in most of the occidental countries. Mammography is one among the key tool to identify the location and size of tumor in the breast. Texture analysis plays an important role in detecting the disease patterns in mammogram and to identify the masses as normal or abnormal. The local binary pattern d...

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...

In this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local binary pattern (LBP) histograms. Unlike most other histogram based invariant texture descriptors which normalize rotation locally, the proposed invariants are constructed globally for the whole region to be described. ...

Both the Local Binary Pattern (LBP) and the Coordinated Clusters Representation (CCR) are two methods used successfully in the classification and segmentation of images. They look very similar at first sight. In this work we analyze the principles of the two methods and show that the methods are not reducible to each other. Topologically they are as different as a sphere and a torus. In extract...

This paper presents a new method for facial expression recognition using divided local binary pattern features. Motivated by Fourier’s parity decomposition, we decompose a LBP descriptor into two subdescriptors. This method reduces the amount of data of the feature extraction, reducing the data dimension effectively. Experimental results on JAFFE facial expression database show that the propose...

In this paper, we propose a new type of local binary pattern (LBP)-based feature, called Rotation Invariant Co-occurrence among adjacent LBPs (RIC-LBP), which simultaneously has characteristics of rotation invariance and a high descriptive ability. LBP was originally designed as a texture description for a local region, called a micropattern, and has been extended to various types of LBP-based ...

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 two novel ways of extending the local binary pattern (LBP) texture analysis operator to multiple scales. First, large-scale texture patterns are detected by combining exponentially growing circular neighborhoods with Gaussian low-pass filtering. Second, cellular automata are proposed as a way of compactly encoding arbitrarily large circular neighborhoods. The performance of ...

In this paper we present a method for objects tracking in images sequence. This approach is achieved into two main steps. In the first one, we constructed the Local Binary Pattern (LBP) histogram pattern of each image in the sequence and the reference pattern. In the second one, we perform the algorithm by the pattern selected based on a distance measures to find similarity between two histogra...