Computer and Robot Vision Vol. 1, by R.M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10887-1.

Computer and Robot Vision

This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

A reflectance model for computer graphics

A smart content-based image retrieval system based on color and texture feature

Digital image libraries and other multimedia databases have been dramatically expanded in recent years. In order to effectively and precisely retrieve the desired images from a large image database, the development of a content-based image retrieval (CBIR) system has become an important research issue. However, most of the proposed approaches emphasize on finding the best representation for different image features. Furthermore, very few of the representative works well consider the user's subjectivity and preferences in the retrieval process. In this paper, a user-oriented mechanism for CBIR method based on an interactive genetic algorithm (IGA) is proposed. Color attributes like the mean value, the standard deviation, and the image bitmap of a color image are used as the features for retrieval. In addition, the entropy based on the gray level co-occurrence matrix and the edge histogram of an image are also considered as the texture features. Furthermore, to reduce the gap between the retrieval results and the users' expectation, the IGA is employed to help the users identify the images that are most satisfied to the users' need. Experimental results and comparisons demonstrate the feasibility of the proposed approach.

A User-Oriented Image Retrieval System Based on Interactive Genetic Algorithm

We present an algorithm of color image understanding which segments the image after analyzing sur-faces with color variations due to lighting condition and object colors. The work is based on dichromaticreflection model according to the strategy of hypothesis plus test, following the continuity of image and thefeature of color clusters, the algorithm completes the image segmentation and gives forth a physical des-cription of imaging process, including intrinsic images, segmented image, the color of light and objects. Re-flecting respectively the propertics of light condition and every objects, both matte image and highlight im-age compose the intrinsic images.

A physical approach to color image understanding

Content based image retrieval using motif cooccurrence matrix

This article introduces two fast algorithms for connected component Labeling of binary images, a peculiar case of coloring. The first one, Selkow DT is pixel-based and a Selkow's algorithm combined with the decision tree optimization technique. The second one called light speed labeling is segment-based line-relative labeling and was especially thought for commodity RISC architectures. An extensive benchmark on both structured and unstructured images substantiates that these two algorithms, the way they were designed, run faster than Wu's algorithm claimed to be the world fastest in 2007. Also they both show greater data independency hence runtime predictability.

Light speed labeling: efficient connected component labeling on RISC architectures

This article introduces a fast algorithm for Connected Component Labeling of binary images called Light Speed Labeling. It is segment-based and a line-relative labeling that was especially thought for RISC computers. An extensive benchmark on both structured and unstructured images substanciates that the algorithm, the way it is designed, is faster and more runtime predictable than Wu's algorithm claimed to be the world fastest in 2007.

Light Speed Labeling for RISC architectures

In this paper, we propose ”stable marriages” algorithms based on a novel representation called marriage table. After explaining how properties as global satisfaction, sex equality and stability show in the representation, we define 3 algorithms corresponding to 3 different scans of the marriage table to meet progressively all constraints. The performance is evaluated in front of the population size for 200 instances in each case. That supports qualitative statistic analysis. Two matching examples in image processing are displayed for illustration.

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A novel representation and algorithms for (quasi) stable marriages

The exponential explosion of images and videos concerns everybody's common life, since this media is now present everywhere and in all human activities. Scientists, artists and engineers, in any field, need to be aware of the basic mechanisms that allow them to understand how images are essentially information carriers. Images bear a strong evocative power, because their perception quickly brings into mind a number of related pictorial contents of past experiences, and even of abstract concepts like pleasure, attraction or aversion. This book analyzes the visual hints, thanks to which, images are generally interpreted, processed and exploited, both by humans and computer programs. Comprehensive introductory text Introduces the reader to the large world of imagery on which many human activities are based, from politics to entertainment, from technical reports to artistic creations Provides a unified framework where both biological and artificial vision are discussed through visual cues, through the role of contexts and the available multi-channels to deliver information

Bertrand Zavidovique

Papers

Content based image retrieval using motif cooccurrence matrix

Light speed labeling: efficient connected component labeling on RISC architectures

Light Speed Labeling for RISC architectures

A novel representation and algorithms for (quasi) stable marriages

3C Vision: Cues, Context and Channels