Modelling, Measuring and Compensating Color Weak Vision

We use methods from Riemann geometry to investigate transformations between the color spaces of color-normal and color weak observers. The two main applications are the simulation of the perception of a color weak observer for a color normal observer and the compensation of color images in a way that a color weak observer has approximately the same perception as a color normal observer. The metrics in the color spaces of interest are characterized with the help of ellipsoids defined by the just-noticable-differences between color which are measured with the help of color-matching experiments. The constructed mappings are isometries of Riemann spaces that preserve the perceived color-differences for both observers. Among the two approaches to build such an isometry, we introduce normal coordinates in Riemann spaces as a tool to construct a global color-weak compensation map. Compared to previously used methods this method is free from approximation errors due to local linearizations and it avoids the problem of shifting locations of the origin of the local coordinate system. We analyse the variations of the Riemann metrics for different observers obtained from new color matching experiments and describe three variations of the basic method. The performance of the methods is evaluated with the help of semantic differential (SD) tests.Comment: Full resolution color pictures are available from the author

A survey of face detection, extraction and recognition

The goal of this paper is to present a critical survey of existing literatures on human face recognition over the last 4-5 years. Interest and research activities in face recognition have increased significantly over the past few years, especially after the American airliner tragedy on September 11 in 2001. While this growth largely is driven by growing application demands, such as static matching of controlled photographs as in mug shots matching, credit card verification to surveillance video images, identification for law enforcement and authentication for banking and security system access, advances in signal analysis techniques, such as wavelets and neural networks, are also important catalysts. As the number of proposed techniques increases, survey and evaluation becomes important

Multimodal Sensory Integration for Perception and Action in High Functioning Children with Autism Spectrum Disorder

Movement disorders are the earliest observed features of autism spectrum disorder (ASD) present in infancy. Yet we do not understand the neural basis for impaired goal-directed movements in this population. To reach for an object, it is necessary to perceive the state of the arm and the object using multiple sensory modalities (e.g. vision, proprioception), to integrate those sensations into a motor plan, to execute the plan, and to update the plan based on the sensory consequences of action. In this dissertation, I present three studies in which I recorded hand paths of children with ASD and typically developing (TD) controls as they grasped the handle of a robotic device to control a cursor displayed on a video screen. First, participants performed discrete and continuous movements to capture targets. Cursor feedback was perturbed from the hand\u27s actual position to introduce visuo-spatial conflict between sensory and proprioceptive feedback. Relative to controls, children with ASD made greater errors, consistent with deficits of sensorimotor adaptive and strategic compensations. Second, participants performed a two-interval forced-choice discrimination task in which they perceived two movements of the visual cursor and/or the robot handle and then indicated which of the two movements was more curved. Children with ASD were impaired in their ability to discriminate movement kinematics when provided visual and proprioceptive information simultaneously, suggesting deficits of visuo-proprioceptive integration. Finally, participants made goal-directed reaching movements against a load while undergoing simultaneous functional magnetic resonance imaging (MRI). The load remained constant (predictable) within an initial block of trials and then varied randomly within four additional blocks. Children with ASD exhibited greater movement variability compared to controls during both constant and randomly-varying loads. MRI analysis identified marked differences in the extent and intensity of the neural activities supporting goal-directed reaching in children with ASD compared to TD children in both environmental conditions. Taken together, the three studies revealed deficits of multimodal sensory integration in children with ASD during perception and execution of goal-directed movements and ASD-related motor performance deficits have a telltale neural signature, as revealed by functional MR imaging

Adaptive Methods for Color Vision Impaired Users

Color plays a key role in the understanding of the information in computer environments. It happens that about 5% of the world population is affected by color vision deficiency (CVD), also called color blindness. This visual impairment hampers the color perception, ending up by limiting the overall perception that CVD people have about the surrounding environment, no matter it is real or virtual. In fact, a CVD individual may not distinguish between two different colors, what often originates confusion or a biased understanding of the reality, including web environments, whose web pages are plenty of media elements like text, still images, video, sprites, and so on. Aware of the difficulties that color-blind people may face in interpreting colored contents, a significant number of recoloring algorithms have been proposed in the literature with the purpose of improving the visual perception of those people somehow. However, most of those algorithms lack a systematic study of subjective assessment, what undermines their validity, not to say usefulness. Thus, in the sequel of the research work behind this Ph.D. thesis, the central question that needs to be answered is whether recoloring algorithms are of any usefulness and help for colorblind people or not. With this in mind, we conceived a few preliminary recoloring algorithms that were published in conference proceedings elsewhere. Except the algorithm detailed in Chapter 3, these conference algorithms are not described in this thesis, though they have been important to engender those presented here. The first algorithm (Chapter 3) was designed and implemented for people with dichromacy to improve their color perception. The idea is to project the reddish hues onto other hues that are perceived more regularly by dichromat people. The second algorithm (Chapter 4) is also intended for people with dichromacy to improve their perception of color, but its applicability covers the adaptation of text and image, in HTML5- compliant web environments. This enhancement of color contrast of text and imaging in web pages is done while keeping the naturalness of color as much as possible. Also, to the best of our knowledge, this is the first web recoloring approach targeted to dichromat people that takes into consideration both text and image recoloring in an integrated manner. The third algorithm (Chapter 5) primarily focuses on the enhancement of some of the object contours in still images, instead of recoloring the pixels of the regions bounded by such contours. Enhancing contours is particularly suited to increase contrast in images, where we find adjacent regions that are color indistinguishable from dichromat’s point of view. To our best knowledge, this is one of the first algorithms that take advantage of image analysis and processing techniques for region contours. After accurate subjective assessment studies for color-blind people, we concluded that the CVD adaptation methods are useful in general. Nevertheless, each method is not efficient enough to adapt all sorts of images, that is, the adequacy of each method depends on the type of image (photo-images, graphical representations, etc.). Furthermore, we noted that the experience-based perceptual learning of colorblind people throughout their lives determines their visual perception. That is, color adaptation algorithms must satisfy requirements such as color naturalness and consistency, to ensure that dichromat people improve their visual perception without artifacts. On the other hand, CVD adaptation algorithms should be object-oriented, instead of pixel-oriented (as typically done), to select judiciously pixels that should be adapted. This perspective opens an opportunity window for future research in color accessibility in the field of in human-computer interaction (HCI).A cor desempenha um papel fundamental na compreensão da informação em ambientes computacionais. Porém, cerca de 5% da população mundial é afetada pela deficiência de visão de cor (ou Color Vision Deficiency (CVD), do Inglês), correntemente designada por daltonismo. Esta insuficiência visual dificulta a perceção das cores, o que limita a perceção geral que os indivíduos têm sobre o meio, seja real ou virtual. Efetivamente, um indivíduo com CVD vê como iguais cores que são diferentes, o que origina confusão ou uma compreensão distorcida da realidade, assim como dos ambientes web, onde existe uma abundância de conteúdos média coloridos, como texto, imagens fixas e vídeo, entre outros. Com o intuito de mitigar as dificuldades que as pessoas com CVD enfrentam na interpretação de conteúdos coloridos, tem sido proposto na literatura um número significativo de algoritmos de recoloração, que têm como o objetivo melhorar, de alguma forma, a perceção visual de pessoas com CVD. Porém, a maioria desses trabalhos carece de um estudo sistemático de avaliação subjetiva, o que põe em causa a sua validação, se não mesmo a sua utilidade. Assim, a principal questão à qual se pretende responder, como resultado do trabalho de investigação subjacente a esta tese de doutoramento, é se os algoritmos de recoloração têm ou não uma real utilidade, constituindo assim uma ajuda efetiva às pessoas com daltonismo. Tendo em mente esta questão, concebemos alguns algoritmos de recoloração preliminares que foram publicados em atas de conferências. Com exceção do algoritmo descrito no Capítulo 3, esses algoritmos não são descritos nesta tese, não obstante a sua importância na conceção daqueles descritos nesta dissertação. O primeiro algoritmo (Capítulo 3) foi projetado e implementado para pessoas com dicromacia, a fim de melhorar a sua perceção da cor. A ideia consiste em projetar as cores de matiz avermelhada em matizes que são melhor percebidos pelas pessoas com os tipos de daltonismo em causa. O segundo algoritmo (Capítulo 4) também se destina a melhorar a perceção da cor por parte de pessoas com dicromacia, porém a sua aplicabilidade abrange a adaptação de texto e imagem, em ambientes web compatíveis com HTML5. Isto é conseguido através do realce do contraste de cores em blocos de texto e em imagens, em páginas da web, mantendo a naturalidade da cor tanto quanto possível. Além disso, tanto quanto sabemos, esta é a primeira abordagem de recoloração em ambiente web para pessoas com dicromacia, que trata o texto e a imagem de forma integrada. O terceiro algoritmo (Capítulo 5) centra-se principalmente na melhoria de alguns dos contornos de objetos em imagens, em vez de aplicar a recoloração aos pixels das regiões delimitadas por esses contornos. Esta abordagem é particularmente adequada para aumentar o contraste em imagens, quando existem regiões adjacentes que são de cor indistinguível sob a perspetiva dos observadores com dicromacia. Também neste caso, e tanto quanto é do nosso conhecimento, este é um dos primeiros algoritmos em que se recorre a técnicas de análise e processamento de contornos de regiões. Após rigorosos estudos de avaliação subjetiva com pessoas com daltonismo, concluiu-se que os métodos de adaptação CVD são úteis em geral. No entanto, cada método não é suficientemente eficiente para todos os tipo de imagens, isto é, o desempenho de cada método depende do tipo de imagem (fotografias, representações gráficas, etc.). Além disso, notámos que a aprendizagem perceptual baseada na experiência das pessoas daltónicas ao longo de suas vidas é determinante para perceber aquilo que vêem. Isto significa que os algoritmos de adaptação de cor devem satisfazer requisitos tais como a naturalidade e a consistência da cor, de modo a não pôr em causa aquilo que os destinatários consideram razoável ver no mundo real. Por outro lado, a abordagem seguida na adaptação CVD deve ser orientada aos objetos, em vez de ser orientada aos pixéis (como tem sido feito até ao momento), de forma a possibilitar uma seleção mais criteriosa dos pixéis que deverão ser sujeitos ao processo de adaptação. Esta perspectiva abre uma janela de oportunidade para futura investigação em acessibilidade da cor no domínio da interacção humano-computador (HCI)

Advances in Image Processing, Analysis and Recognition Technology

For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches

Automated image-based quality control of molecularly imprinted polymer films

We present results of applying a feature extraction process to images of coatings of molecularly imprinted polymers (MIPs) coatings on glass substrates for defect detec- tion. Geometric features such as MIP side lengths, aspect ratio, internal angles, edge regularity, and edge strength are obtained by using Hough transforms, and Canny edge detection. A Self Organizing Map (SOM) is used for classification of texture of MIP surfaces. The SOM is trained on a data set comprised of images of manufactured MIPs. The raw images are first processed using Hough transforms and Canny edge detection to extract just the MIP-coated portion of the surface, allowing for surface area estimation and reduction of training set size. The training data set is comprised of 20-dimensional feature vectors, each of which is calculated from a single section of a gray scale image of a MIP. Haralick textures are among the quantifiers used as feature vector components. The training data is then processed using principal component analysis to reduce the number of dimensions of the data set. After training, the SOM is capable of classifying texture, including defects

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

Feature-based image patch classification for moving shadow detection

Moving object detection is a first step towards many computer vision applications, such as human interaction and tracking, video surveillance, and traffic monitoring systems. Accurate estimation of the target object’s size and shape is often required before higher-level tasks (e.g., object tracking or recog nition) can be performed. However, these properties can be derived only when the foreground object is detected precisely. Background subtraction is a common technique to extract foreground objects from image sequences. The purpose of background subtraction is to detect changes in pixel values within a given frame. The main problem with background subtraction and other related object detection techniques is that cast shadows tend to be misclassified as either parts of the foreground objects (if objects and their cast shadows are bonded together) or independent foreground objects (if objects and shadows are separated). The reason for this phenomenon is the presence of similar characteristics between the target object and its cast shadow, i.e., shadows have similar motion, attitude, and intensity changes as the moving objects that cast them. Detecting shadows of moving objects is challenging because of problem atic situations related to shadows, for example, chromatic shadows, shadow color blending, foreground-background camouflage, nontextured surfaces and dark surfaces. Various methods for shadow detection have been proposed in the liter ature to address these problems. Many of these methods use general-purpose image feature descriptors to detect shadows. These feature descriptors may be effective in distinguishing shadow points from the foreground object in a specific problematic situation; however, such methods often fail to distinguish shadow points from the foreground object in other situations. In addition, many of these moving shadow detection methods require prior knowledge of the scene condi tions and/or impose strong assumptions, which make them excessively restrictive in practice. The aim of this research is to develop an efficient method capable of addressing possible environmental problems associated with shadow detection while simultaneously improving the overall accuracy and detection stability. In this research study, possible problematic situations for dynamic shad ows are addressed and discussed in detail. On the basis of the analysis, a ro bust method, including change detection and shadow detection, is proposed to address these environmental problems. A new set of two local feature descrip tors, namely, binary patterns of local color constancy (BPLCC) and light-based gradient orientation (LGO), is introduced to address the identified problematic situations by incorporating intensity, color, texture, and gradient information. The feature vectors are concatenated in a column-by-column manner to con struct one dictionary for the objects and another dictionary for the shadows. A new sparse representation framework is then applied to find the nearest neighbor of the test image segment by computing a weighted linear combination of the reference dictionary. Image segment classification is then performed based on the similarity between the test image and the sparse representations of the two classes. The performance of the proposed framework on common shadow detec tion datasets is evaluated, and the method shows improved performance com pared with state-of-the-art methods in terms of the shadow detection rate, dis crimination rate, accuracy, and stability. By achieving these significant improve ments, the proposed method demonstrates its ability to handle various problems associated with image processing and accomplishes the aim of this thesis

The effect of work related mechanical stress on the peripheral temperature of the hand

The evolution and developments in modern industry have resulted a wide range of occupational activities, some of which can lead to industrial injuries. Due to the activities of occupational medicine, much progress has been made in transforming the way that operatives perform their tasks. However there are still many occupations where manual tasks have become more repetitive, contributing to the development of conditions that affect the upper limbs. Repetitive Strain Injury is one classification of those conditions which is related to overuse of repetitive movement. Hand Arm Vibration Syndrome is a subtype of this classification directly related to the operation of instruments and machinery which involves vibration. These conditions affect a large number of individuals, and are costly in terms of work absence, loss of income and compensation. While such conditions can be difficult to avoid, they can be monitored and controlled, with prevention usually the least expensive solution. In medico-legal situations it may be difficult to determine the location or the degree of injury, and therefore determining the relevant compensation due is complicated by the absence of objective and quantifiable methods. This research is an investigation into the development of an objective, quantitative and reproducible diagnostic procedure for work related upper limb disorders. A set of objective mechanical provocation tests for the hands have been developed that are associated with vascular challenge. Infrared thermal imaging was used to monitor the temperature changes using a well defined capture protocol. Normal reference values have been measured and a computational tool used to facilitate the process and standardise image processing. These objective tests have demonstrated good discrimination between groups of healthy controls and subjects with work related injuries but not individuals, p<0.05, and are reproducible. A maximum value for thermal symmetry of 0.5±0.3ºC for the whole upper limbs has been established for use as a reference. The tests can be used to monitor occupations at risk, aiming to reduce the impact of these conditions, reducing work related injury costs, and providing early detection. In a medico-legal setting this can also provide important objective information in proof of injury and ultimately in objectively establishing whether or not there is a case for compensation