A very simple but efficient feature descriptor is proposed for image matching/registration applications where invariance is not important. The descriptor length is only three times the height of the local region in which the descriptor is calculated, and experiments were conducted to compare it to the SURF descriptor. In addition, it is shown, how the sampling can be modified in order to obtain...

Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...

The paper presents an efficient and reliable feature descriptor for human detection in a top-view depth image that uses two statistical values of mean and standard deviation. Human detection performance of our descriptor outperform Rauter that use mean value and Simplified Local Ternary Pattern (SLTP). To evaluate the human detection performance using our descriptor, we capture 559 positive and...

Face Recognition with Learning-based Descriptor. 1The Chinese University of Hong Kong. Xiaoou Tang1, 3.We pdf converter for linux free download examine the building blocks of descriptor algorithms and evaluate numerous. Mations and can be compared with other descriptors in a database to obtain.Several versions of the revised Descriptors were consulted on widely with stakeholders and users of th...

Multi-lingual multi-script often poses various challenges in handwritten numeral classification. In this paper, we present a method for classification of off-line handwritten numerals of three popular Indian scripts. Here we consider Kannada, Telugu and Tamil scripts for our experiment. The features used in the classifier are obtained from local intensity order patter descriptor. For feature co...

In this paper, a new texture descriptor based on the local neighborhood intensity difference is proposed for content based image retrieval (CBIR). For computation of texture features like Local Binary Pattern (LBP), the center pixel in a 3×3 window of an image is compared with all the remaining neighbors, one pixel at a time to generate a binary bit pattern. It ignores the effect of the adjacen...

The purpose of this paper is to detect human in images. This paper proposes a method for extracting human body feature descriptors consisting of projected edge component series. The feature descriptor can express appearances and shapes of human with local and global distribution of edges. Our method evaluated with a linear SVM classifier on Daimler-Chrysler pedestrian dataset, and test with var...

This paper introduces a shape descriptor based on a combination of topological image analysis and texture information. Critical points of a shape’s skeleton are determined first. The shape is described according to persistence of the local topology at these critical points over a range of scales. The local topology over scale-space is derived using the local binary pattern texture operator with...

This paper proposes a novel local feature descriptor, Local Directional Number Pattern (LDN), for face analysis: face and expression recognition. LDN encodes the directional information of the face’s textures (i.e., the texture’s structure) in a compact way, producing a more discriminative code than current methods. We compute the structure of each micro-pattern with the aid of a compass mask, ...

Osteoarthritis (OA) causes progressive degeneration of articular cartilage and pathological changes in subchondral bone. These changes can be assessed volumetrically using micro-computed tomography (μCT) imaging. The local descriptor, i.e. local binary pattern (LBP), is a new alternative solution to perform analysis of local bone structures from μCT scans. In this study, different trabecular bo...