Shape analysis using multiresolution gradient vector field

TL;DR: Four key strategies are proposed to incorporate ligature-sensitive information into the part decomposition and shape matching processes and show that the incorporation of these strategies significantly improves the retrieval accuracy when applied to LEMS's 99 and 216 silhouette database.

TL;DR: Examples of useful strategies that can be employed to improve the performance of shape matching algorithms are described, which significantly improves shape database retrieval accuracy.

TL;DR: This chapter discusses two Dimensional Systems and Mathematical Preliminaries and their applications in Image Analysis and Computer Vision, as well as image reconstruction from Projections and image enhancement.

TL;DR: A summary of the layout of cortical areas associated with vision and with other modalities, a computerized database for storing and representing large amounts of information on connectivity patterns, and the application of these data to the analysis of hierarchical organization of the cerebral cortex are reported on.

TL;DR: It is shown that recognition of geometrical patterns and alphabetical characters independently of position, size and orientation can be accomplished and it is indicated that generalization is possible to include invariance with parallel projection.

TL;DR: This paper presents work on computing shape models that are computationally fast and invariant basic transformations like translation, scaling and rotation, and proposes shape detection using a feature called shape context, which is descriptive of the shape of the object.