Object recognition has become one of the most active research topics in computer vision in recent years. The set of features extracted from the training image is critical for good object recognition performance. The Scale Invariant Feature Transform (SIFT) was proposed by David Lowe in 1999; the SIFT features are local and effective for object recognition. In this paper we conducted a survey of...

In recent years, Lowe’s Scale Invariant Feature Transform (SIFT) algorithm has become a widely used tool for object recognition. One shortcoming is that it only works on grayscale image intensities. In this paper, we propose extending the SIFT descriptor to also incorporate color information in a novel fashion. The keypoint descriptor proposed in this paper is a superset of the original feature...

background: one of the challenges of pet/mri combined systems is to derive an attenuation map to correct the pet image. for that, the pseudo-ct image could be used to correct the attenuation. until now, most existing scientific researches construct this pseudo-ct image using the registration techniques. however, these techniques suffer from the local minima of the non-rigid deformation energy f...

Shape description is one of the key parts of image content description for image retrieval. Most of existing shape descriptors are usually either application dependent or non-robust, making them undesirable for generic shape description. In this paper, a generic Fourier descriptor (GFD) is proposed to overcome the drawbacks of existing shape representation techniques. The proposed shape descrip...

3D object retrieval has received much research attention during the last years. To automatically determine the similarity between 3D objects, the global descriptor approach is very popular, and many competing methods for extracting global descriptors have been proposed to date. However, no single descriptor has yet shown to outperform all other descriptors on all retrieval benchmarks or benchma...

In this paper, a new texture descriptor based on the local neighborhood intensity difference is proposed for content based image retrieval (CBIR). For computation of texture features like Local Binary Pattern (LBP), the center pixel in a 3×3 window of an image is compared with all the remaining neighbors, one pixel at a time to generate a binary bit pattern. It ignores the effect of the adjacen...

This paper presents an overview of color and texture descriptors that have been approved for the Final Committee Draft of the MPEG-7 standard. The color and texture descriptors that are described in this paper have undergone extensive evaluation and development during the past two years. Evaluation criteria include effectiveness of the descriptors in similarity retrieval, as well as extraction,...

Local image descriptors are generally designed for describing all possible image patches. Such patches may be subject to complex variations in appearance due to incidental object, scene and recording conditions. Because of this, a single-best descriptor for accurate image representation under all conditions does not exist. Therefore, we propose to automatically select from a pool of descriptors...