Segmentation of images by color features: a survey

En este articulo se hace la revisión del estado del arte sobre la segmentación de imagenes de colorImage segmentation is an important stage for object recognition. Many methods have been proposed in the last few years for grayscale and color images. In this paper, we present a deep review of the state of the art on color image segmentation methods; through this paper, we explain the techniques based on edge detection, thresholding, histogram-thresholding, region, feature clustering and neural networks. Because color spaces play a key role in the methods reviewed, we also explain in detail the most commonly color spaces to represent and process colors. In addition, we present some important applications that use the methods of image segmentation reviewed. Finally, a set of metrics frequently used to evaluate quantitatively the segmented images is shown

Engineering data compendium. Human perception and performance. User's guide

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use

Semantik renk değişmezliği

Color constancy aims to perceive the actual color of an object, disregarding the effectof the light source. Recent works showed that utilizing the semantic information inan image enhances the performance of the computational color constancy methods.Considering the recent success of the segmentation methods and the increased numberof labeled images, we propose a color constancy method that combines individualilluminant estimations of detected objects which are computed using the classes of theobjects and their associated colors. Then we introduce a weighting system that valuesthe applicability of the object classes to the color constancy problem. Lastly, weintroduce another metric expressing the detected object and how well it fits the learnedmodel of its class. Finally, we evaluate our proposed method on a popular colorconstancy dataset, confirming that each weight addition enhances the performanceof the global illuminant estimation. Experimental results show promising results,outperforming the conventional methods while competing with the state of the artmethods.--M.S. - Master of Scienc

TWO-ILLUMINANT ESTIMATION AND USER-PREFERRED CORRECTION FOR IMAGE COLOR CONSTANCY

Master'sMASTER OF SCIENC

Engineering Data Compendium. Human Perception and Performance, Volume 1

The concept underlying the Engineering Data Compendium was the product an R and D program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design of military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by system designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is Volume 1, which contains sections on Visual Acquisition of Information, Auditory Acquisition of Information, and Acquisition of Information by Other Senses

Robot vision - Color based human tracking using the UV model

Master'sMASTER OF ENGINEERIN

Effects of resolution of lighting control systems

Advances in lighting technologies have spurred sophisticated lighting control systems (LCSs). To conserve energy and improve occupants’ wellbeing, LCSs have been integrated into sustainable buildings. However, the complexity of LCSs may lead to negative experiences and reduce the frequency of their use. One fundamental issue, which has not been systematically investigated, is the impact of control resolution (the smallest change produced by an LCS). In an ideal LCS, the resolution would be sufficiently fine for users to specify their desired lighting conditions, but the smallest change would be detectable. Thus, the design of optimal control systems requires a thorough understanding of the detectability and acceptability of differences in illuminance, luminance and colour. The control of colour is complicated by the range of interfaces that can be used to facilitate colour mixing. Four psychophysical experiments investigated the effect of LCS resolution. The first two experiments explored the effect of resolution in white light LCSs on usability and energy conservation. The results suggest that, in different applications, LCSs with resolutions between 14.8 % and 17.7 % (of illuminance) or 26.0 % and 32.5 % (of luminance) have the highest usability. The third experiment evaluated the usability of three colour channel control interfaces based on red, green, blue (RGB), hue, saturation, brightness (HSB) and opponent colour mixing systems. Although commonly used, the RGB interface was found to have the lowest usability. The fourth experiment explored the effect of hue resolution, saturation resolution and luminance resolution on the usability. Generally, middle range resolutions, which are approximately between three and five times the magnitude of the just noticeable difference (JND), for both hue and saturation were found to yield the greatest usability. The interaction between these three variables was characterised. Findings from this research provide a deeper understanding of the fundamental attribute of control resolution and can guide the development of useful and efficient lighting control systems

Object and feature based modelling of attention in meeting and surveillance videos

MPhilThe aim of the thesis is to create and validate models of visual attention. To this extent, a novel unsupervised object detection and tracking framework has been developed by the author. It is demonstrated on people, faces and moving objects and the output is integrated in modelling of visual attention. The proposed approach integrates several types of modules in initialisation, target estimation and validation. Tracking is rst used to introduce high-level features, by extending a popular model based on low-level features[1]. Two automatic models of visual attention are further implemented. One based on winner take it all and inhibition of return as the mech- anisms of selection on a saliency model with high- and low-level features combined. Another which is based only on high-level object tracking results and statistic proper- ties from the collected eye-traces, with the possibility of activating inhibition of return as an additional mechanism. The parameters of the tracking framework thoroughly investigated and its success demonstrated. Eye-tracking experiments show that high- level features are much better at explaining the allocation of attention by the subjects in the study. Low-level features alone do correlate signi cantly with real allocation of attention. However, in fact it lowers the correlation score when combined with high-level features in comparison to using high-level features alone. Further, ndings in collected eye-traces are studied with qualitative method, mainly to discover direc- tions in future research in the area. Similarities and dissimilarities between automatic models of attention and collected eye-traces are discusse