A novel real-time local visual feature, namely FAST+LBP, is proposed in this paper for omnidirectional vision. It combines the advantages of two computationally simple operators by using Features from Accelerated Segment Test (FAST) as the feature detector and Local Binary Patterns (LBP) operator as the feature descriptor. The matching experiments of the panoramic images from the COLD database ...

In this paper, we propose a simple and robust local descriptor, called the robust local binary pattern (RLBP). The local binary pattern (LBP) works very successfully in many domains, such as texture classification, human detection and face recognition. However, an issue of LBP is that it is not so robust to the noise present in the image. We improve the robustness of LBP by changing the coding ...

A machine vision based approach for classification of tobacco leaves for automatic harvesting in a complex agricultural environment is proposed in this paper. The CIELAB color space model is used to segment the leaf from the background. The segmented leaves are classified into three classes viz., ripe, unripe, and over-ripe. Models based on various textural features such as GLTP (Gray Level Loc...

Texture is an important characteristic for many types of images. In recent years very discriminative and computationally efficient local texture descriptors based on local binary patterns (LBP) have been developed, which has led to significant progress in applying texture methods to different problems and applications. Due to this progress, the division between texture descriptors and more gene...

In this paper we propose to use local binary patterns (LBP) as features in a classi cation framework for classifying di erent texture patterns in lung computed tomography. Image intensity is included by means of the joint LBP and intensity histogram, and classi cation is performed using the k nearest neighbor classi er with histogram similarity as distance measure. The proposed method is evalua...

Facial micro-expression recognition is an upcoming area in computer vision research. Up until the recent emergence of the extensive CASMEII spontaneous micro-expression database, there were numerous obstacles faced in the elicitation and labeling of data involving facial micro-expressions. In this paper, we propose the Local Binary Patterns with Six Intersection Points (LBP-SIP) volumetric desc...

In this paper we propose to use local binary patterns (LBP) as features in a classification framework for classifying different texture patterns in lung computed tomography. Image intensity is included by means of the joint LBP and intensity histogram, and classification is performed using the k nearest neighbor classifier with histogram similarity as distance measure. The proposed method is ev...

The offline signature verification is an automatic verification system that works on the scanned image of a signature. Signature verification uses the gray level measure with varying foreground features. The signature verification is performed by identifying feature vector using local patterns. The Local Binary Pattern (LBP) in signature verification has used to extract the local structure info...

I-Abstract Human detection is a key problem in computer vision, which is widely used in image analysis, intelligent vehicle and visual surveillance. However, the task of human detection is rather challenging because of high variations of clothing, pose, occlusion, scale and illumination. In human detection systems, feature extraction and learning method are two important parts and hot research ...

This paper investigates and compares the performance of local descriptors for race classification from face images. Two powerful types of local descriptors have been considered in this study: Local Binary Patterns (LBP) and Weber Local Descriptors (WLD). First, we investigate the performance of LBP and WLD separately and experiment with different parameter values to optimize race classification...