Figural object models represent object shape in terms of a hierarchy of simple shapes, protrusions, and indentations that we call "figures". Each figure has an unbranching, coarsely sampled net of medial primitives which carr>.: width information. The figural hierarchy and its medial primitives thus define the boundary with a -tolerance proportional to the corresponding medial widths, and assoc...

This paper presents a new method for image retrieval using a graph object oriented database for processing the information extracted from the image through the segmentation process and through the semantic interpretation of this information. The object oriented database schema is structured as a classes hierarchy based on graph data structure. A graph structure is used in all phases of the imag...

The contribution deals with the contextual design of spatial data for the purposes of the regional development, land management and government, describes the role of remote sensing data and contextual modelling for the context oriented geo-information and tries to provide the framework for the object hierarchy of classes and propose the ways of structure and behaviour modelling. The digital geo...

We present a modular architecture for image understanding and active computer vision which consists of three major components: Sensor and actor interfaces required for data{driven active vision are encapsulated to hide machine{dependent parts; image segmentation is implemented in object{ oriented programming as a hierarchy of image operator classes, guaranteeing simple and uniform interfaces; k...

Recently recognition and categorization of objects from images using local features has become very popular. While similar approaches have been used for identification and categorization tasks they have not been treated in a common framework. In this paper we present a method that treats visual object identification, categorization in a common framework by exploiting ideas from image interclass...

This paper presents a novel algorithm to build hierarchies from independent component analyzer mixtures and its application to image similarity measure. The hierarchy algorithm composes an agglomerative (bottom-up) clustering from the estimated parameters (basis vectors and bias terms) of the ICA mixture. Merging at different levels of the hierarchy is made using the Kullback-Leibler distance b...

This paper presents an overview of the work we have done over the last several years on object recognition in images from region-based image representation. The overview focuses on the following related problems: (1) discovery of a single 2D object category frequently occurring in a given image set; (2) learning a model of the discovered category in terms of its photometric, geometric, and stru...

Most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. To solve the problem, this paper utilizes Zernike Moment (ZM) and Pseudo Zernike Moment (PZM) to extract object contour features in all situations such as rotation, scaling and shifting of object i...

Abstract   In this paper, we propose a new method for kernel based object tracking which tracks the complete non rigid object. Definition the union image blob and mapping it to a new representation which we named as potential pixels matrix are the main part of tracking algorithm. The union image blob is constructed by expanding the previous object region based on the histogram feature. The pote...

Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this work, we are proposing an ...