Differential feature distribution maps for image segmentation and region queries in image databases

Abstract

We present a novel region segmentation framework, dedicated to region queries in content-based image retrieval. Some of the features that are considered for image indexing are used for segmenting the image in a few regions of interest. The novelty of our technique comes from the unification of the feature-space and the image-space segmentation in a common framework. The method uses no prior modeling of the image, focusing on local feature distributions and their spatial stability in a multi-feature, multi-resolution approach. Several experiments are presented on real-world imagery, demonstrating the power of the method for segmentation and region queries in image databases.

Genetic coding of image on synthetic peptides

“…Segmentation Pretreatment. We use the method proposed by Winter and Nastar (1999). This method is essentially based on the notion of a Differential Feature Distribution Map (DFDM), which measures the local stability of feature distribution in a given image, with the help of a block of neighboring pixels.…”

Modular Statistical Optimization and VQ Method for Image Recognition

“…Several features extraction techniques are developed and used in images recognition systems. The extracted features vary from the low to the high level image description (color, shape, geometry, semantic knowledge... etc) [5,6,7]. These techniques often differ by their results quality obtained in various applications.…”