Comparison of Different Classifiers and the Majority Voting Rule for the Detection of Plum Fruits in Garden Conditions

Color segmentation is one of the most thoroughly studied problems in agricultural applications of remote image capture systems, since it is the key step in several different tasks, such as crop harvesting, site specific spraying, and targeted disease control under natural light. This paper studies and compares five methods to segment plum fruit images under ambient conditions at 12 different light intensities, and an ensemble method combining them. In these methods, several color features in different color spaces are first extracted for each pixel, and then the most effective features are selected using a hybrid approach of artificial neural networks and the cultural algorithm (ANN-CA). The features selected among the 38 defined channels were the b* channel of L*a*b*, and the color purity index, C*, from L*C*h. Next, fruit/background segmentation is performed using five classifiers: artificial neural network-imperialist competitive algorithm (ANN-ICA); hybrid artificial neural network-harmony search (ANN-HS); support vector machines (SVM); k nearest neighbors (kNN); and linear discriminant analysis (LDA). In the ensemble method, the final class for each pixel is determined using the majority voting method. The experiments showed that the correct classification rate for the majority voting method excluding LDA was 98.59%, outperforming the results of the constituent methods.This research was funded by the Spanish MICINN, as well as European Commission FEDER funds, under grant RTI2018-098156-B-C53. This project has also been supported by the European Union (EU) under Erasmus+ project entitled "Fostering Internationalization in Agricultural Engineering in Iran and Russia" [FARmER] with grant number 585596-EPP-1-2017-1-DE-EPPKA2-CBHE-JP

Camera based Display Image Quality Assessment

This thesis presents the outcomes of research carried out by the PhD candidate Ping Zhao during 2012 to 2015 in Gjøvik University College. The underlying research was a part of the HyPerCept project, in the program of Strategic Projects for University Colleges, which was funded by The Research Council of Norway. The research was engaged under the supervision of Professor Jon Yngve Hardeberg and co-supervision of Associate Professor Marius Pedersen, from The Norwegian Colour and Visual Computing Laboratory, in the Faculty of Computer Science and Media Technology of Gjøvik University College; as well as the co-supervision of Associate Professor Jean-Baptiste Thomas, from The Laboratoire Electronique, Informatique et Image, in the Faculty of Computer Science of Universit´e de Bourgogne. The main goal of this research was to develop a fast and an inexpensive camera based display image quality assessment framework. Due to the limited time frame, we decided to focus only on projection displays with static images displayed on them. However, the proposed methods were not limited to projection displays, and they were expected to work with other types of displays, such as desktop monitors, laptop screens, smart phone screens, etc., with limited modifications. The primary contributions from this research can be summarized as follows: 1. We proposed a camera based display image quality assessment framework, which was originally designed for projection displays but it can be used for other types of displays with limited modifications. 2. We proposed a method to calibrate the camera in order to eliminate unwanted vignetting artifact, which is mainly introduced by the camera lens. 3. We proposed a method to optimize the camera’s exposure with respect to the measured luminance of incident light, so that after the calibration all camera sensors share a common linear response region. 4. We proposed a marker-less and view-independent method to register one captured image with its original at a sub-pixel level, so that we can incorporate existing full reference image quality metrics without modifying them. 5. We identified spatial uniformity, contrast and sharpness as the most important image quality attributes for projection displays, and we used the proposed framework to evaluate the prediction performance of the state-of-the-art image quality metrics regarding these attributes. The proposed image quality assessment framework is the core contribution of this research. Comparing to conventional image quality assessment approaches, which were largely based on the measurements of colorimeter or spectroradiometer, using camera as the acquisition device has the advantages of quickly recording all displayed pixels in one shot, relatively inexpensive to purchase the instrument. Therefore, the consumption of time and resources for image quality assessment can be largely reduced. We proposed a method to calibrate the camera in order to eliminate unwanted vignetting artifact primarily introduced by the camera lens. We used a hazy sky as a closely uniform light source, and the vignetting mask was generated with respect to the median sensor responses over i only a few rotated shots of the same spot on the sky. We also proposed a method to quickly determine whether all camera sensors were sharing a common linear response region. In order to incorporate existing full reference image quality metrics without modifying them, an accurate registration of pairs of pixels between one captured image and its original is required. We proposed a marker-less and view-independent image registration method to solve this problem. The experimental results proved that the proposed method worked well in the viewing conditions with a low ambient light. We further identified spatial uniformity, contrast and sharpness as the most important image quality attributes for projection displays. Subsequently, we used the developed framework to objectively evaluate the prediction performance of the state-of-art image quality metrics regarding these attributes in a robust manner. In this process, the metrics were benchmarked with respect to the correlations between the prediction results and the perceptual ratings collected from subjective experiments. The analysis of the experimental results indicated that our proposed methods were effective and efficient. Subjective experiment is an essential component for image quality assessment; however it can be time and resource consuming, especially in the cases that additional image distortion levels are required to extend the existing subjective experimental results. For this reason, we investigated the possibility of extending subjective experiments with baseline adjustment method, and we found that the method could work well if appropriate strategies were applied. The underlying strategies referred to the best distortion levels to be included in the baseline, as well as the number of them

The development of multi-channel inkjet printing methodologies for fine art applications

This thesis contributes to the defence of the practitioner perspective as a means of undertaking problems addressed predominantly in the field of colour science. Whilst artists have been exploring the use of colour for centuries through their personal practice and education, the rise of industrialised printing processes has generated a shift in focus away from these creative pursuits and into the computational field of colour research. It is argued here that the disposition and knowledge generated by creative practice has significant value to offer developing technologies. While creative practice has limited influence in the development of colour printing, practitioners and users of technology actively engage with the process in ways that extend beyond its intended uses in order to overcome recognised shortcomings. Here consideration is given to this creative engagement as motivation to develop bespoke printing parameters that demonstrate the effects of colour mixing through methods alternative to standard workflows. The research is undertaken incorporating both qualitative and quantitative analysis, collecting data from visual assessments and by examining spectral measurements taken from printed output. Action research is employed to directly access and act upon the constant developments in the art and science disciplines related to inkjet printing, observing and engaging with current methods and techniques employed by practitioners and developers. This method of research has strongly informed the empirical testing that has formed this thesis’s contribution to fine art inkjet printing practice. The research follows a practitioner led approach to designing and testing alternative printing methods and is aimed at expanding the number of discernible colours an inkjet printer can reproduce. The application of this methodology is evidenced through demonstrative prints and a reproduction study undertaken at the National Gallery, London. The experimentation undertaken in partnership with the National Gallery has proven the ability to increase accuracy between colour measured from the original target and reproduction, beyond the capabilities of current inkjet printing workflows

NON-INVASIVE IMAGE ENHANCEMENT OF COLOUR RETINAL FUNDUS IMAGES FOR A COMPUTERISED DIABETIC RETINOPATHY MONITORING AND GRADING SYSTEM

Diabetic Retinopathy (DR) is a sight threatening complication due to diabetes mellitus affecting the retina. The pathologies of DR can be monitored by analysing colour fundus images. However, the low and varied contrast between retinal vessels and the background in colour fundus images remains an impediment to visual analysis in particular in analysing tiny retinal vessels and capillary networks. To circumvent this problem, fundus fluorescein angiography (FF A) that improves the image contrast is used. Unfortunately, it is an invasive procedure (injection of contrast dyes) that leads to other physiological problems and in the worst case may cause death. The objective of this research is to develop a non-invasive digital Image enhancement scheme that can overcome the problem of the varied and low contrast colour fundus images in order that the contrast produced is comparable to the invasive fluorescein method, and without introducing noise or artefacts. The developed image enhancement algorithm (called RETICA) is incorporated into a newly developed computerised DR system (called RETINO) that is capable to monitor and grade DR severity using colour fundus images. RETINO grades DR severity into five stages, namely No DR, Mild Non Proliferative DR (NPDR), Moderate NPDR, Severe NPDR and Proliferative DR (PDR) by enhancing the quality of digital colour fundus image using RETICA in the macular region and analysing the enlargement of the foveal avascular zone (F AZ), a region devoid of retinal vessels in the macular region. The importance of this research is to improve image quality in order to increase the accuracy, sensitivity and specificity of DR diagnosis, and to enable DR grading through either direct observation or computer assisted diagnosis system

Configural and perceptual factors influencing the perception of color transparency

The mechanisms by which the brain represents colors are largely unknown. In addition, the large number of color phenomena in the natural world has made understanding color rather difficult. Color transparency perception, which is studied in this thesis, is precisely one of these interesting phenomena: when a surface is seen both in plain view and through a transparent overlay, the visual system still identifies it as a single surface. Processes of the visual system have widely inspired researchers in many domains such as neurosciences, psychology, as well as computer vision. The progress of digital imaging technologies requires research engineers to deal with issues that demand knowledge of human visual processing. To humans, an image is not a random collection of pixels, but a meaningful arrangement of regions and objects. One thus can be inspired by the human visual system to investigate color representation and its applicability to digital image processing. Finding a model of perception is still a challenging matter for researchers among multidisciplinary fields. This thesis discusses the problem of defining an accurate model of transparency perception. Despite the large number of studies on this topic, the underlying mechanisms are still not well understood. Investigating perceptual transparency is challenging due to its interactions with different visual phenomena, but the most intensively studied conditions for perceptual transparency are those involving achromatic luminance and chromatic constraints. Although these models differ in many aspects, a broad distinction can be drawn between models of additive and subtractive transparency. The General Convergence Model (GCM) combines both additive and subtractive color mixtures in showing that systematic chromatic changes in a linear color space, such as translation and convergence (or a combination of both), lead to perceptual transparency. However, while this model seems to be a necessary condition, it is not a sufficient one for transparency perception. A first motivation of this thesis was to evaluate and define situations more general than the GCM. Several chromatic changes consistent or not with the GCM were generated. Additional parameters, such as configural complexity, luminance level, magnitude of the chromatic change and shift direction were tested. The main results showed that observers' responses are influenced by each of the above cited parameters. Convergences appear significantly more transparent when motion is added for bipartite configurations, or when they are generated in a checkerboard configuration. Translations are influenced by both configuration and motion. Shears are described as opaque, except when short vector lengths are combined with motion: the overlay tends to be transparent. Divergences are strongly affected by motion and vector lengths, and rotations by a combination of checkerboard configuration with luminance level and vector length. These results question the generality of the GCM. We also investigated the effects of shadows on the perception of a transparent filter. An attempt to extend these models to handle transparency perception in complex scenes involving surfaces varying in shape and depth, change in conditions of illumination and shadow, is described. A lightness-matching task was performed to evaluate how much constancy is shown by the subject among six experimental conditions, in which shadow position, shadow blur, shadow and filter blending values were varied. The results showed that lightness constancy is very high even if surfaces were seen under both filter and shadow. A systematic deviation from perfect constancy in a manner consistent with a perceived additive shift was also observed. Because the GCM includes additive mixture and is related to color and lightness constancy, these results are promising and may be explained ultimately by this model

NON-INVASIVE IMAGE ENHANCEMENT OF COLOUR RETINAL FUNDUS IMAGES FOR A COMPUTERISED DIABETIC RETINOPATHY MONITORING AND GRADING SYSTEM

Diabetic Retinopathy (DR) is a sight threatening complication due to diabetes mellitus affecting the retina. The pathologies of DR can be monitored by analysing colour fundus images. However, the low and varied contrast between retinal vessels and the background in colour fundus images remains an impediment to visual analysis in particular in analysing tiny retinal vessels and capillary networks. To circumvent this problem, fundus fluorescein angiography (FF A) that improves the image contrast is used. Unfortunately, it is an invasive procedure (injection of contrast dyes) that leads to other physiological problems and in the worst case may cause death. The objective of this research is to develop a non-invasive digital Image enhancement scheme that can overcome the problem of the varied and low contrast colour fundus images in order that the contrast produced is comparable to the invasive fluorescein method, and without introducing noise or artefacts. The developed image enhancement algorithm (called RETICA) is incorporated into a newly developed computerised DR system (called RETINO) that is capable to monitor and grade DR severity using colour fundus images. RETINO grades DR severity into five stages, namely No DR, Mild Non Proliferative DR (NPDR), Moderate NPDR, Severe NPDR and Proliferative DR (PDR) by enhancing the quality of digital colour fundus image using RETICA in the macular region and analysing the enlargement of the foveal avascular zone (F AZ), a region devoid of retinal vessels in the macular region. The importance of this research is to improve image quality in order to increase the accuracy, sensitivity and specificity of DR diagnosis, and to enable DR grading through either direct observation or computer assisted diagnosis system

Publicaciones y ponencias - 2004 -

This document presents the list of publications and presentations done by the EAFIT teaching and administrative staff in the year 2004. The information is organized alphabetically by Research Groups of the corresponding Schools. The contributions appear in alphabetical order in the following sequence: international and national publications, and international and national presentations. The publications include books, chapters of books, and articles. The  presentations include conferences, congresses, and general academic events. The majority of these presentations have been published in the proceedings of the corresponding event.Este documento presenta la relación de publicaciones y ponencias realizadas por los profesores y personal administrativo de la Universidad EAFIT en el año 2004. La información está organizada por Grupos de Investigación dentro de cada una de las Escuelas. Cada contribución aparece en orden alfabético dentro de la correspondiente categoría de la siguiente secuencia: publicaciones internacionales, publicaciones nacionales, ponencias internacionales y ponencias nacionales. En las publicaciones están comprendidos los libros, capítulos de libros y artículos de revista. Las ponencias relacionan las presentaciones en conferencias, congresos y eventos de divulgación. La mayoría de estas presentaciones figuran, tal como se indica en cada caso, publicadas como parte de las memorias del evento respectivo

Annotation sémantique 2D/3D d'images spatialisées pour la documentation et l'analyse d'objets patrimoniaux

In the field of architecture and historic preservation , the information and communication technologies enable the acquisition of large amounts of data introducing analysis media for different purposes and at different levels of details ( photographs, point cloud, scientific imaging, ...). The organization and the structure of these resources is now a major problem for the description, the analysis and the understanding of cultural heritage objects. However the existing solutions in semantic annotations on images or on 3D model are insufficient, especially in the linking of different analysis media.This thesis proposes an approach for conducting annotations on different two-dimensional media while allowing the propagation of these annotations between different representations (2D or 3D) of the object. The objective is to identify solutions to correlate (from a spatial, temporal and semantic point of view) sets of annotations within sets of images. Thus, the system is based on the principle of data spatialization for establishing a relationship between the 3D representations, incorporating all the geometric complexity of the object and therefore to the metric information extraction, and 2D representations of object. The approach seeks to the establishment of an information continuity from the image acquisition to the construction of 3D representations semantically enhanced by incorporating multi-media and multi-temporal aspects. This work resulted in the definition and the development of a set of software modules that can be used by specialists of conservation of architectural heritage as by the general public.Dans le domaine de l’architecture et de la conservation du patrimoine historique, les technologies de l’information et de la communication permettent l’acquisition de grandes quantités de données introduisant des supports d’analyses pour différentes finalités et à différents niveaux de détails (photographies, nuages de points, imagerie scientifique, …). L’organisation et la structuration de ces ressources est aujourd’hui un problème majeur pour la description, l’analyse et la compréhension d’objets patrimoniaux. Cependant les solutions existantes d’annotations sémantiques d’images ou de modèle 3D se révèlent insuffisantes notamment sur l’aspect de mise en relation des différents supports d’analyse.Cette thèse propose une approche permettant de conduire des annotations sur les différents supports bidimensionnels tout en permettant la propagation de ces annotations entre les différentes représentations (2D ou 3D) de l’objet. L’objectif est d’identifier des solutions pour corréler (d’un point de vue spatial, temporel et sémantique) des jeux d’annotations au sein d’un jeu d’images. Ainsi le système repose sur le principe de spatialisation des données permettant d’établir une relation entre les représentations 3D, intégrant toute la complexité géométrique de l’objet et par conséquent permettant l’extraction d’informations métriques, et les représentations 2D de l’objet. L’approche cherche donc à la mise en place d’une continuité informationnelle depuis l’acquisition d’images jusqu’à la construction de représentations 3D sémantiquement enrichies en intégrant des aspects multi-supports et multi-temporels. Ce travail a abouti à la définition et le développement d’un ensemble de modules informatiques pouvant être utilisés par des spécialistes de la conservation d’un patrimoine architectural comme par le grand public