Evaluation of interest point detectors for image information extraction

Comparing and Evaluating Interest Points

Many computer vision tasks rely on feature extraction. Interest points are such features. This paper shows that interest points are geometrically stable under diierent transformations and have high information content (distinctiveness). These two properties make interest points very successful in the context of image matching. To measure these two properties quantitatively, we introduce two eva...

Performance Evaluation of Local Detectors in the Presence of Noise for Multi-Sensor Remote Sensing Image Matching

Automatic, efficient, accurate, and stable image matching is one of the most critical issues in remote sensing, photogrammetry, and machine vision. In recent decades, various algorithms have been proposed based on the feature-based framework, which concentrates on detecting and describing local features. Understanding the characteristics of different matching algorithms in various applications ...

Visual Interest point detection based Rank Order Log filter for Content Based Image Retrieval

With increased digital images in image repositories efficient indexing and searching becomes essential for large image archives. Content based image retrieval system (CBIR) retrieve relevant images using low-level features like color, texture and shape for image representation. In this approach, a scheme of novel color image retrieval based on visual interest point is presented. The existing sy...

A Filtering Strategy for Interest Point Detecting to Improve Repeatability and Information Content

This paper compares several stereo image interest point detectors with respect to their repeatability and information content through experimental analysis. The Harris-Laplace detector gives better results than other detectors in areas of good texture; however, in areas of poor texture, the HarrisLaplace detector may be not the best choice. A featurerelated filtering strategy is designed for th...

Evaluation of interest point detectors in content-based image retrieval