An object location strategy using shape and grey-level models

An Object Location Strategy using Shape and Grey-level Models

Any model-based image interpretation system must be capable of describing objects, whose appearance in real images can vary widely, in sufficient detail to ensure that robust location of objects is possible. The system must cope with circumstances where data is incomplete, for example when touching and occlusion occur. We argue that to achieve this it is necessary to describe grey-level propert...

Statistical Grey-Level Models for Object Location and Identification

This paper presents a new method for modelling and locating objects in images for applications such as Printed Circuit Board (PCB) inspection. Objects of interest are assumed to exhibit little variation in size or shape from one example to the next, but may vary considerably in grey-level appearance. Simple correlation based approaches perform poorly on such examples. We demonstrate how a stati...

Recognising Human Faces Using Shape and Grey - Level Information

Object Location Control Using Meta-level Programming

In distributed environments, location control of objects among hosts is a crucial concern. This paper proposes a new mechanism of object location control using meta-level programming which provides the following advantages to programmers. First, the description of location control can be separated from the application program by exploiting the meta-level architecture. This separation makes it e...

Active Shape Model Search using Local Grey-Level Models: A Quantitative Evaluation

We describe methods for locating known structures in images. We have previously described statistical models of shape and shape variability which can be used for this purpose (Active Shape Models). In this paper we show how statistical models of grey-level appearance can be incorporated, leading to improved reliability and accuracy. We describe experiments designed to (i) test how well an ASM c...