Color-based object recognition: Analysis and application

A novel indoor color-based object recognition algorithm is presented in response to the challenges posed by the current machine vision research status. Previous researches found that current color constancy technique are inadequate in dealing with color object recognition. Furthermore, researches in...

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Main Author: Reyes, Napoleon H.
Format: text
Language:English
Published: Animo Repository 2004
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Online Access:https://animorepository.dlsu.edu.ph/etd_doctoral/940
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1939&context=etd_doctoral
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_doctoral-19392022-03-28T08:58:33Z Color-based object recognition: Analysis and application Reyes, Napoleon H. A novel indoor color-based object recognition algorithm is presented in response to the challenges posed by the current machine vision research status. Previous researches found that current color constancy technique are inadequate in dealing with color object recognition. Furthermore, researches in the field of fuzzy multi-channel color imaging are rather sparse. Contrary to color constancy algorithms, the algorithm develop focuses on manipulating a color locus depicting the color locus depicting the colors of an object (mobile robot), and not stabilizing the whole image appearance per se. The rationale behind the development of the new color object recognition algorithm is inspired by recent findings in the neurophysiological aspect of the human visual system, which suggests that contrast computation precedes segmentation. This research contributes in the field of Color Science by providing a new set of color descriptors that adheres to human perception of color, in a new transformed rg-chromaticity space. Moreover, this research extends the computing prowess of fuzzy logic in the realm of multi-channel color imaging by providing a new breed of gradually adaptive multi-channel fuzzy color inferential filter for color locus constancy, called Reyes-Dadios Color Contrast Fusion (RDCCF). RDCCF utilizes a new color contrast degrade operator that was originally mathematically derived in this work, along with color contrast enhance. RDCCF is the first of its kind in the family of true fuzzy inferential filters for tracking down objects via color. The RDCCF algorithm locks on a color locus depicting the target object, whilw accurately compensating for the effects of glare, and hue and saturation drifts. Experiments on color spotting similar (hue-related) colors show that the new color decriptors and RDCCF combined, is better than using rectangular and pie-slice decision regions in UV space. In addition, this research provides an algorithm for recognizing mobile robots even in the event of collisions. Also, this work presents an algorithm for predicting the position of the ball. Empirical results of the application of the color-based object recognition algorithm on the robot soccer game attest to its robustness under spatially varying illumination intensities, multiple light sources, presence of highlights, object rotation and collision, in real-time. 2004-04-19T07:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etd_doctoral/940 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1939&context=etd_doctoral Dissertations English Animo Repository Colors Computer algorithms Fuzzy logic Computer Sciences
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Colors
Computer algorithms
Fuzzy logic
Computer Sciences
spellingShingle Colors
Computer algorithms
Fuzzy logic
Computer Sciences
Reyes, Napoleon H.
Color-based object recognition: Analysis and application
description A novel indoor color-based object recognition algorithm is presented in response to the challenges posed by the current machine vision research status. Previous researches found that current color constancy technique are inadequate in dealing with color object recognition. Furthermore, researches in the field of fuzzy multi-channel color imaging are rather sparse. Contrary to color constancy algorithms, the algorithm develop focuses on manipulating a color locus depicting the color locus depicting the colors of an object (mobile robot), and not stabilizing the whole image appearance per se. The rationale behind the development of the new color object recognition algorithm is inspired by recent findings in the neurophysiological aspect of the human visual system, which suggests that contrast computation precedes segmentation. This research contributes in the field of Color Science by providing a new set of color descriptors that adheres to human perception of color, in a new transformed rg-chromaticity space. Moreover, this research extends the computing prowess of fuzzy logic in the realm of multi-channel color imaging by providing a new breed of gradually adaptive multi-channel fuzzy color inferential filter for color locus constancy, called Reyes-Dadios Color Contrast Fusion (RDCCF). RDCCF utilizes a new color contrast degrade operator that was originally mathematically derived in this work, along with color contrast enhance. RDCCF is the first of its kind in the family of true fuzzy inferential filters for tracking down objects via color. The RDCCF algorithm locks on a color locus depicting the target object, whilw accurately compensating for the effects of glare, and hue and saturation drifts. Experiments on color spotting similar (hue-related) colors show that the new color decriptors and RDCCF combined, is better than using rectangular and pie-slice decision regions in UV space. In addition, this research provides an algorithm for recognizing mobile robots even in the event of collisions. Also, this work presents an algorithm for predicting the position of the ball. Empirical results of the application of the color-based object recognition algorithm on the robot soccer game attest to its robustness under spatially varying illumination intensities, multiple light sources, presence of highlights, object rotation and collision, in real-time.
format text
author Reyes, Napoleon H.
author_facet Reyes, Napoleon H.
author_sort Reyes, Napoleon H.
title Color-based object recognition: Analysis and application
title_short Color-based object recognition: Analysis and application
title_full Color-based object recognition: Analysis and application
title_fullStr Color-based object recognition: Analysis and application
title_full_unstemmed Color-based object recognition: Analysis and application
title_sort color-based object recognition: analysis and application
publisher Animo Repository
publishDate 2004
url https://animorepository.dlsu.edu.ph/etd_doctoral/940
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1939&context=etd_doctoral
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