Yining Deng

An efficient color representation for image retrieval

A compact color descriptor and an efficient indexing method for this descriptor are presented. The target application is similarity retrieval in large image databases using color. Colors in a given region are clustered into a small number of representative colors. The feature descriptor consists of the representative colors and their percentages in the region. A similarity measure similar to the quadratic color histogram distance measure is defined for this descriptor. The representative colors can be indexed in the three-dimensional (3-D) color space thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The matches from all of the query colors are then combined to obtain the final retrievals. An efficient indexing scheme for fast retrieval is presented. Experimental results show that this compact descriptor is effective and compares favorably with the traditional color histogram in terms of overall computational complexity.

Peer group filtering and perceptual color image quantization

In the first part of this work, peer group filtering (PGF), a nonlinear algorithm for image smoothing and impulse noise removal in color images is presented. The algorithm replaces each image pixel with the weighted average of its peer group members, which are classified based on the color similarity of the neighboring pixels. Results show that it effectively removes the noise and smooths the color images without blurring edges and details. In the second part of the work, PGF is used as a preprocessing step for color quantization. Local statistics obtained after PGF are used as weights in the quantization to suppress color clusters in detailed regions, since human perception is less sensitive to the differences in these areas. As a result, very coarse quantization can be obtained while preserving the color information in the original images. This can be useful in color image segmentation and color image retrieval applications.

An efficient low-dimensional color indexing scheme for region-based image retrieval

In this work, an efficient low-dimensional color indexing scheme for region-based image retrieval is presented. The colors in each image region are first quantized so that only a small number of cluster centroids are needed to represent the region color information. The proposed color feature descriptor consists of these quantized colors and their percentages in the region. A similarity distance measure is defined and shown to be equivalent to the quadratic color histogram distance measure. The quantized colors are indexed in the 3-D color space so that high-dimensional indexing can be avoided. During the search process, each quantized color in the query is used as a separate cue to find matches containing that color. The matches from all the query colors are then joined to obtain the final retrievals. Experimental results show that the proposed scheme is fast and accurate compared to the color histogram approach.

Managing and searching personal photo collections

We present a prototype system for managing and searching collections of personal digital images. The system allows the collection to be stored across a mixture of local and remote computers and managed seamlessly. It provides multiple ways of organizing and viewing the same collection. It also provides a search function that uses features based on face detection and low-level color, texture and edge features combined with digital camera capture settings to provide high-quality search that is computed at the server but available from all other networked devices accessing the photo collection. Evaluations of the search facility using human relevancy experiments are provided.

Issues for image/video digital libraries

Creation of digital image and video libraries poses several interesting and challenging problems. New tools are needed for managing such multimedia content. These include methods to search, retrieve, and manipulate digital media by using the media content information and mechanisms to protect intellectual property rights. This paper outlines some of the recent advances in image processing as related to digital libraries in the context of the UCSB Alexandria Digital Library project.