SIFT-like representations are considered as being most resistant to common deformations, although their computational burden is heavy for low-computation applications such as mobile image retrieval. H. Bay et. al. proposed an efficient implementation of SIFT called SURF. Although this descriptor has been able to represent the nature of some underlying image patterns, it is not enough to represe...

a r t i c l e i n f o Extracting local keypoints and keypoint descriptions from images is a primary step for many computer vision and image retrieval applications. In the literature, many researchers have proposed methods for representing local texture around keypoints with varying levels of robustness to photometric and geometric transformations. Gradient-based descriptors such as the Scale In...

It is well recognized that image representation is the most fundamental task of the face recognition, effective and efficient image feature extraction not only has small intraclass variations and large interclass similarity but also robust to the impact of pose, illumination, expression and occlusion. This paper proposes a new local image descriptor for face recognition, named Log–Gabor Weber d...

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...

Maintenance of digital image libraries requires to frequently asses the quality of the images to engage preservation measures if necessary. We present an approach to image based quality assurance for digital image collections based on local descriptor matching. We use spatially distinctive local keypoints of contrast enhanced images and robust symmetric descriptor matching to calculate affine t...

Many recent applications using local image features focus on 2D image recognition. Such applications can not distinguish between real objects and photos of objects. In this project, we present a 3D object recognition method using stereo images. Using the 3D information of the objects obtained from stereo images, objects with similar image description but different 3D shapes can be distinguished...

The purpose of this paper is to show how the edge histogram descriptor for image that can be efficiently utilized for image matching. Since the edge histogram descriptor recommended for the standard represents only local edge distribution in an image, the matching performance for image retrieval may not be satisfactory. In this paper, to increase the matching performance, we propose to use the ...

We propose a compact descriptor for the purpose of dense image matching and object recognition. The descriptor is calculated based on local gradients about each point in an image. It contains the averages of gradients at four different windows surrounding a center point. The descriptor is calculated much faster than histogram of oriented gradients (HOG). Additionally, it will be shown that it i...