Texture is an important image feature and is defined as something consisting of mutually related elements. Texture based classification is an important approach for effective object recognition in digital images. This paper presents an efficient approach for texture classification based on local directional binary patterns (LDBP) and nonsubsampled contourlet transform (NSCT). The NSCT has trans...

Previous mining algorithms on high dimensional datasets, such as biological dataset, create very large patterns sets as a result which includes small and discontinuous sequential patterns. These patterns do not bear any useful information for usage. Mining sequential patterns in such sequences need to consider different forms of patterns, such as contiguous patterns, local patterns which appear...

Texture is a rich source of visual information about the surface characteristics of an object in the digital image. So texture characteristics play an important role in texture image classification. In this paper, we propose a novel approach of texture image classification based on nonsubsampled contourlet transform (NSCT) and local directional binary patterns (LDBP). The NSCT has translation i...

The singular points of fingerprints, namely core and delta, play an important role in fingerprint recognition and classification systems. Several traditional methods have been proposed; however, these methods cannot achieve the reliable and accurate detection of poor-quality fingerprints. In this paper, an algorithm is proposed which combines improved Poincaré index and multi-resolution analysi...

We propose a technique for recovering the position and depth of pronuclei of human zygotes, from z-stacks acquired using Hoffman Modulation Contrast microscopy. We use Local Binary Pattern features for describing local texture, and integrate information from multiple neighboring areas of the stack, including those where the object to be detected would appear defocused; interestingly, such defoc...

2 Are built upon powerful patch-based (local) image models:  Non-Local Means (NLM): self-similarity within natural images  K-SVD: sparse representation modeling of image patches  BM3D: combines a sparsity prior and non local self-similarity  Kernel-regression: offers a local directional filter  EPLL: exploits a GMM model of the image patches  … Today we present a way to improve various su...

The selection of valuable features is crucial in pattern recognition. In this paper we deal with the issue that part of features originate from directional instead of common linear data. Both for directional and linear data a theory for a statistical modeling exists. However, none of these theories gives an integrated solution to problems, where linear and directional variables are to be combin...

Email: [email protected] [email protected] References Simulating global illumination demands for solving the lighting integral of a surface point. Ambient Occlusion (AO): pro: appealing approximation of local occlusion con: no directional information (static gray shadows) Screen Space Directional Occlusion (SSDO) [Ritschel09]: pro: combination of occlusion sampling a...