Toward color image segmentation in analog VLSI: Algorithm and hardware

Standard techniques for segmenting color images are based on finding normalized RGB discontinuities, color histogramming, or clustering techniques in RGB or CIE color spaces. The use of the psychophysical variable hue in HSI space has not been popular due to its numerical instability at low saturations. In this article, we propose the use of a simplified hue description suitable for implementation in analog VLSI. We demonstrate that if theintegrated white condition holds, hue is invariant to certain types of highlights, shading, and shadows. This is due to theadditive/shift invariance property, a property that other color variables lack. The more restrictive uniformly varying lighting model associated with themultiplicative/scale invariance property shared by both hue and normalized RGB allows invariance to transparencies, and to simple models of shading and shadows. Using binary hue discontinuities in conjunction with first-order type of surface interpolation, we demonstrate these invariant properties and compare them against the performance of RGB, normalized RGB, and CIE color spaces. We argue that working in HSI space offers an effective method for segmenting scenes in the presence of confounding cues due to shading, transparency, highlights, and shadows. Based on this work, we designed and fabricated for the first time an analog CMOS VLSI circuit with on-board phototransistor input that computes normalized color and hue

Color in computer vision

The use of colour in computer vision has received growing attention . This paper gives the state-of-art in this subfield, and tries to answer the questions : What is color ? Which are the adequate representations ? How to compute it ? What can be donc, using it ? Towards that goal, we make a deep and up-to-date review of the existing litterature on this subject, we ondine the important research directions and issues, and we attempt to evaluate them .L'utilisation de la couleur en vision par ordinateur est un sujet de recherche qui suscite un intérêt croissant . Ce papier fait le point dans ce domaine, en essayant de répondre aux questions : Qu'est-ce que la couleur ? Quelles en sont les représentations adéquates ? Comment la déterminer ? Que peut-on en faire ? Pour cela, nous faisons une revue approfondie et très à jour de l'ensemble de la littérature consacrée à ce sujet en cernant les axes de recherche et les problématiques importantes et en tentant de les évaluer

Use of Colour in Machine Vision: Colour Representation, Edge Detection with Colour, Segmentation of Colour Space and Colour Constancy

This report is a study of the role of colour and its use in machine vision. Intuitively, for low level image processing, colour provides greater discrimination than grey level for separating different homogenous regions in an image. The first part describes the use of colour in edge detection. In current vision systems, extracting object features such as lines and arcs relies on edge detection. The use of colour images (RGB) can offer additional confidence in the existence of an edge element in one plane when it is corroborated by pixels at the location on one or more of the other planes. The second part investigates the problems and techniques associated with colour image segmentation. A spectral segmentation algorithm based on locating the boundaries of each colour cluster in the spectral space is proposed. The third part investigates the use of colour features for object recognition. Colour information also provides a useful cue for object localisation and identification. The major issues that have to be addressed are colour constancy and representation, and also, their connections to segmentation. Finally, a system for locating object surfaces based on a simplified colour constancy and its colour representation is proposed