Canonical forms attempt to factor out a non-rigid shape’s pose, giving a pose-neutral shape. This opens up the possibility of using methods originally designed for rigid shape retrieval for the task of non-rigid shape retrieval. We extend our recent benchmark for testing canonical form algorithms. Our new benchmark is used to evaluate a greater number of state-of-the-art canonical forms, on fiv...

The problem of efficiently finding images that are similar to a target image has attracted much attention in the image processing community and is rightly considered an information retrieval task. However, the problem of finding structure and regularities in large image datasets is an area in which data mining is beginning to make fundamental contributions. In this work, we consider the new pro...

We have previously published a multiresolution approach for the shape similarity comparison of polygon soup 3D models. The approach combined a single-resolution shape feature with a multiresolution representation produced by using the 3D alpha shapes algorithm of Edelsbrunner for the shape similarity comparison. The study evaluated the efficacy of the multiresolution shape comparison approach b...

This paper presents a 2D shape retrieval system using moment invariants based on a representation of image boundary of the shape objects. The original binary image is transformed into a matrix which consists of numbers that represents the distance to the shape contour. Chessboard distance transform is used for the representation of the shape contour. Moment invariants are computed for the origi...

Most Content-Based Image Retrieval (CBIR) systems employ color as primary feature with texture and shape as secondary features. Very few systems exploit spatial features. None of the available systems combines all three visual features, texture, shape and location, for organization and retrieval. Moreover relatively few systems use Gabor filters in texture extraction, despite the widely acclaim...

The objective of this track is to evaluate the performance of 3D shape retrieval approaches on a large-sale comprehensive 3D shape database that contains different types of models, such as generic, articulated, CAD and architecture models. The track is based on a new comprehensive 3D shape benchmark, which contains 8,987 triangle meshes that are classified into 171 categories. The benchmark was...

In this paper, we present a new and effective color image retrieval scheme for combining all the three i.e. color, texture and shape information, which achieved higher retrieval efficiency. Firstly, the image is predetermined by using fast color quantization algorithm with clusters merging, and then a small number of dominant colors and their percentages can be obtained. Secondly, the spatial t...

In this paper we present the results of the Shape Retrieval Contest’10 (SHREC’10) of Generic 3D Warehouse. The aim of this track was to evaluate the performances of various 3D shape retrieval algorithms on a large Generic benchmark based on the Google 3D Warehouse. We hope that the benchmark developed at NIST will provide valuable contributions to the 3D shape retrieval community. Three groups ...

In this paper, we present the efficient content based image retrieval systems which employ the color, texture and shape information of images to facilitate the retrieval process. For efficient feature extraction, we extract the color, texture and shape feature of images automatically using edge detection which is widely used in signal processing and image compression. For facilitated the speedy...

Geometric moment invariants (GMIs) have been widely used as basic tool in shape analysis and information retrieval. Their structure and characteristics determine efficiency and effectiveness. Two fundamental building blocks or generating functions (GFs) for invariants are discovered, which are dot product and vector product of point vectors in Euclidean space. The primitive invariants (PIs) can...