A robust and effective feature map integration method is presented for infrared (IR) target recognition. Noise in an IR image makes a target recognition system unstable in pose estimation and shape matching. A cooperative feature map binding under computational Gestalt theory shows robust shape matching properties in noisy conditions. The pose of a 3D target is estimated using a Markov Chain Mo...

We consider the problem of learning an object model for feature matching. The matching system is Bayesian in nature with separate likelihood and prior parts. The likelihood is based on Gabor filter responses, which are modelled as probability distributions in the filter response vector space. The prior model for the object shape is learnt in two stages: in the first stage we assume only the mea...

For a given visual feature, due to the diversity of hu-man's subjective judgment, a visual information retrieval system that supports a single preexed similarity measure will result in poor retrieval performance. To address this problem, this paper proposes the concept of similarity matching toolkit which consists of different similarity measures simulating human's perceptions of the given feat...

Similarity-based retrieval from shape databases typically employs a pairwise shape matcher and one or more indexing techniques. In this paper, we focus specifically on the design of a pairwise matcher for retrieval of 2-D shape contours. In the past, the matchers used for the oneto-many problem of shape retrieval were often designed for the problem of matching an isolated pair of shapes. This a...

For a given visual feature, due to the diversity of human's subjective judgment, a visual information retrieval system that supports a single pre xed similarity measure will result in poor retrieval performance. To address this problem, this paper proposes the concept of similarity matching toolkit which consists of different similarity measures simulating human's perceptions of the given featu...

Correlation Functions: Thus far, we have either extended the applicability of standard condensed matter order parameters and correlation functions by incorporating shape matching, or applied standard shape matching applications directly in the context of assembled systems. However, in addition to extending existing applications for use with assembled systems, shape matching allows us to invent ...

Content Based Image Retrieval (CBIR) system is an approach to search images and retrieve relevant images from image databases using visual content (information) of an image. In today’s scenario, CBIR receives a query object as input and retrieves similar objects as output from an image database according to a similarity/distance measure. Generally, color, texture, shapes or any combinations of ...

This paper presents an application of a flexible model-based template matching algorithm named "deformable template matching." The template which models the shape of objects consists of some nodal points and segments that connect the nodal points sequentially. The template holds information about the known deformation of the object's shape, and it makes the shape recognition flexible. The match...

This paper compares two methods for object localization from contours: shape context and chamfer matching of templates. In the light of our experiments, we suggest improvements to the shape context: Shape contexts are used to find corresponding features between model and image. In real images it is shown that the shape context is highly influenced by clutter, furthermore even when the object is...

Images may be matched as whole images or using shape matching. Shape matching requires: identifying edges in the image, finding shapes using the edges and representing the shapes using a suitable metric. A Laplacian edge detector is simple and efficient for identifying the edges of shapes. Chain codes describe shapes using sequences of numbers and may be matched simply, accurately and flexibly....