Development of areal time color classifier to robotics applications / Desenvolvimento de um sistema de classificação de cores em tempo real para aplicações robóticas

AUTOR(ES)
DATA DE PUBLICAÇÃO

2008

RESUMO

In computer vision, the detection of objects is a task of great importance. We can verify this by the existence of several methods proposed in the literature. Each one of these methods is based on some characteristics present in the image to reach an eficient performance. Considering environments that make use of colors for determining the objects present in a image, it is possible to utilize them as the characteristics that allow to detect the objects. In this work, two color classifiers are investigated. The first one is based on the thresholding in the HSV space and the second is constituted by a self-organizing map for classifying of pixels in the RGB space. Aiming to construct an eficient color classifier able to process video in real time, it is proposed a technique that is based on the quantization concept. It is also investigated the detection of movement to avoid processing undesired points. The performance of the color classifier system is validated in a MIROSOT robot soccer environment, which is a dynamic environment, requiring that all image processing be very fast in order to detect all the objects present in each frame. The results show that the color classifier system is able to detect correctly all objects present in the robot soccer environment, processing each frame in less than 30 milliseconds, turning the developed system very appropriate for real time video processing

ASSUNTO(S)

real time computer vision redes neurais visão computacional neural networks mapa auto-organizável self organizing maps tempo real

ACESSO AO ARTIGO

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