This paper proposes a novel method for texture classification using high-order local pattern descriptor: Local Derivative Pattern (LDP). LDP is used to encode directional pattern features based on local derivative variations. The nth order LDP is proposed to encode the (n-1)th order local derivative direction variations, which can capture more detailed information. The local texture information...

-This paper proposes a method for extracting GLCM Features on Local Directional Pattern based Fuzzy Co-occurrence matrix for effective face recognition. In this method Local Directional Pattern is computed on the image and then fuzzy representation is used for reduction of image edge responsiveness values. Contrast, correlation, energy and homogeneity features are evaluated over Co-occurrence m...

Facial expression recognition, as one of the important topics in pattern recognition and computer vision, has broad applications in fields of human-computer interaction, psychological behavior analysis, image understanding. This paper presents a novel facial expression recognition method based on global and local features extraction and facial recognition using decision-level fusion. We first e...

In this paper, we develop a stochastic, discrete, structured metapopulation model to explore the dynamics and patterns of biodiversity of riparian vegetation. In the model, individual plants spread along a branched network via directional dispersal and undergo neutral ecological drift. Simulation results suggest that in comparison to 2-D landscapes with non-directional dispersal, river networks...

In literature of face recognition many methods have been proposed which extract features at multiple scales for robust classification. In this paper, we proposed a novel method which utilizes Local Polynomial Approximation (LPA) techniques to capture the directional information of the face image at different scales. LPA based filters are used to obtain directional faces from the normalized face...

In this work, a novel approach is proposed to recognize some facial expressions from time-sequential depth videos. Local Directional Pattern (LDP) features are extracted from the time-sequential depth faces that are followed by Linear Discriminant Analysis (LDA) to make the features more robust. Finally, the robust local features are applied with Hidden Markov Models (HMMs) for facial expressio...