Texture is one of the chief characteristics of an image. In recent years, local texture descriptors have garnered attention among researchers in describing effective texture patterns to demarcate facial images. A feature descriptor titled Local Texture Description Framework-based Modified Local Directional Number pattern (LTDF_MLDN), capable of encoding texture patterns with pixels that lie at ...

As a regional feature, texture is a description of the spatial distribution of the image pixels. As texture can fully utilize the image information, it can become an important basis to describe and recognize the image. Compared with other image features, texture can take both the macro image properties and micro structure into consideration; therefore, feature has become a significant feature t...

Traditional image texture measure usually allows a texture description of a single band of the spectrum, characterizing the spatial variability of gray-level values within the singleband image. A problem with the approach while applied to multispectral images is that it only uses the texture information from selected bands. In this paper, we propose a new multivariate texture measure based on t...

In this paper we present a framework for estimating corrupted coefficients in multiple description coding (MDC) of images. Descriptions are generated by partitioning the domain of wavelet coefficients into sets whose elements are maximally separated from each other. Consequently an edge-adaptive estimation algorithm is proposed to explore the local texture statistical characteristics for estima...

Research is taking place to find effective algorithms for content-based image representation and description. There is a substantial amount of algorithms available that use visual features (color, shape, texture). Shape feature has attracted much attention from researchers that there are many shape representation and description algorithms in literature. These shape image representation and des...

We present a novel multi-shot re-identification method, that merges together two different pattern recognition paradigms for describing objects: feature-based and relation-based. The former aims at encoding visual properties that characterize the object per se. The latter gives a relational description of the object considering how the visual properties are interdependent. The method considers ...

Texture segmentation is an important task in image processing. The objective is to assign the same value to those pixels in an image which belong to the same texture. This is usually called pixel-classification. There exist two fundamental approaches to solve this task. The first and most general approach we call classification oriented by which we mean that the actual labeling is done by some ...

Odors are often difficult to describe verbally, and little is known about the association of odors with words that them. Following literature on crossmodal correspondences between sounds/haptics, this study aimed reveal how associated describing textures haptics in Japanese language. Fifty participants smelled 17 food-related (e.g., lemon, pepper) matched related texture sakusaku), soft, dry), ...

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture ...