Point Extraction Research Articles

A new method for extracting and representing object contours in real images

This paper introduces a new operator for the calculation of the brightness gradient (derived from the Compass gradient) and a new methodology based on a fuzzy algorithm for extraction of the contour points of objects in a real image. A bidimensional geometrical representation of the contours thus extracted is then given in the form of arcs and segments in order to exploit this simplified description as an index for a search in a database of 3-D primitives. The procedure described gives good results, even in the presence of juxtaposed surfaces of the same nature and color, or with contours which do not contrast very well.

A stereo matching paradigm based on the Walsh transformation

Describes a new feature-based stereo matching technique which exploits the Walsh transformation. The established matching strategy adopts and integrates the fundamental steps of the stereo vision problem: (a) detecting and locating feature points, (b) searching for potential matches, (c) validating a match through a global consistency check, and (d) determining the disparity of the matched feature points. The unique representation of stereo images into Walsh-based attributes unites the aforementioned steps into an integrated process which yields accurate disparity extraction. It is shown that the first and second Walsh attributes are used as operators approximating the first and second derivatives for the extraction and localization of feature points. The complete set of these attributes are then used as matching primitives contributing equally to the decision-making process and providing relevant information on both the characterization of a potential match and its validation through a consistency check. Computer results using images of varying complexities prove the soundness and the relatively fast processing time of this stereo matching technique. >

Automatic feature point extraction on a human face in model-based image coding

A preliminary version of a feature point extractor is proposed. In existing model-based coding systems, the feature points of the human face are extracted manually. To make model-based image coding more practical, a coder that can automatically extract the feature points must be developed. We define an ideal feature point extractor and discuss both the requirements and problems. A preliminary solution has been implemented. The proposed feature point extractor can automatically extract the feature points of eyebrows, eyes, the outline of a face, and some other useful information. It can be combined with model-based image coding and used in the video phone/conference systems.