The present paper put forward efficient content-based image retrieval (CBIR) system by extracting structural, texture and local features from images. The local features are extracted from local directional pattern (LDP). The LDP produces a steady local edge response in the presence of noise, illumination changes. The LDP coded image is converted in to a ternary pattern image based on a threshol...

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...

This paper presents a novel feature descriptor termed principal component analysis (PCA)-based Advanced Local Octa-Directional Pattern (ALODP-PCA) for content-based image retrieval. The conventional approaches compare each pixel of an with certain neighboring pixels providing discrete information. proposed in this work utilizes the local intensity all eight directions its neighborhood. octa-dir...

Face recognition is becoming very popular tools for a successful human commuter interaction system. It seems to be a good compromise between reliability and social acceptance and balances security and privacy well. In this paper, we have presented a new appearance-based feature descriptor, the local directional pattern Variance (LDPv), to represent facial components and analyzed its performance...

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, ...

Face recognition is still a very demanding area of research. This problem becomes more challenging in unconstrained environment and in the presence of several variations like pose, illumination, expression, etc. Local descriptors are widely used for this task. The existing local descriptors are not able to utilize the wider local information to make the descriptor more discriminative. The wider...

 Abstract— The local descriptors have gained wide range of attention due to their enhanced discriminative abilities. It has been proved that the consideration of multi-scale local neighborhood improves the performance of the descriptor, though at the cost of increased dimension. This paper proposes a novel method to construct a local descriptor using multi-scale neighborhood by finding the lo...

-In this paper, we investigate a new approach for personal authentication using Finger-Knuckle-Print through a novel texture descriptor, Local Directional Pattern (LDP). The image is encoded with Local Directional Pattern, which enhances the information as each pixel is represented as a binary LDP code. The Finger-Knuckle-Print is divided into smaller areas and LDP histograms are extracted from...

in this paper, a novel directional super wide band micro strip antenna based on a simple and new geometry has been proposed. the antenna exhibits the widest bandwidth ever reported to the authors’ knowledge from 50 ghz to 200 ghz. its radiation pattern is approximately steady in the frequency ranges of 50 ghz to 200 ghz. the antenna consists of a club-like radiating patch, a combination of thre...