This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The...

In this paper, we proposed a system of automatically classifying different types of dates from their images. Different dates have various distinguished features that can be useful to recognize a particular date. These features include color, texture, and shape. In the proposed system, a color image of a date is decomposed into its color components. Then, local texture descriptor in the form of ...

Abstrct The detection of ground plane and free space remains challenging for non-flat plane, especially with the varying latitudinal and longitudinal slope or in the case of multi-ground plane. In this paper, we propose a framework of the ground plane detection with stereo vision. The main contribution of this paper is a newly proposed descriptor which is implemented in the disparity image to o...

A new method to describe sperm vitality using a hybrid combination of local and global texture descriptors is proposed in this paper. In this regard, a new adaptive local binary pattern (ALBP) descriptor is presented in order to carry out the local description. It is built by adding oriented standard deviation information to an ALBP descriptor in order to achieve a more complete representation ...

Depth scans acquired from different views may contain nuisances such as noise, occlusion, and varying point density. We propose a novel Signature of Geometric Centroids descriptor, supporting direct shape matching on the scans, without requiring any preprocessing such as scan denoising or converting into a mesh. First, we construct the descriptor by voxelizing the local shape within a uniquely ...

A new method to describe texture images using a hybrid combination of local and global texture descriptors is proposed in this paper. In this regard, a new adaptive local binary pattern (ALBP) descriptor is presented in order to carry out the local description. It is built by adding oriented standard deviation information to an ALBP descriptor in order to achieve a more complete representation ...

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...

Introduction. Recently, a comparative study in [2] has shown the superior performance of local features for face recognition in unconstrained environments. Due to the global integration of Speeded Up Robust Features (SURF) [1], the authors claim that it stays more robust to various image perturbations than the more locally operating SIFT descriptor. However, no detailed analysis for a SURF base...

Local Binary Pattern (LBP) are considered as a classical descriptor for texture analysis, it has mostly been used in pattern recognition and computer vision applications. However, the LBP gets information from restricted number of local neighbors which is not enough to describe information, other descriptors that get large suffer dimensionality consume much time. In this regard, we propose nove...