Pattern Recognition for Micro Workpieces Manufacturing
Reconocimiento de Patrones para la Fabricación de Microobjetos
Tatiana Baidyk1, Ernst Kussul1, Oleksandr Makeyev2 and Graciela Velasco1
1 Center of Applied Science and Technological Development, National Autonomous University of Mexico (UNAM), tbaidyk@servidor.unam.mx , ekussul@servidor.unam.mx , graciela.velasco@ccadet.unam.mx.
2 Department of Electrical and Computer Engineering, Clarkson University, USA, mckehev@hotmail.com.
]]>Article received on June 13, 2008
Accepted on April 3, 2009
Abstract
Two neural classifiers were developed for image recognition: PCNC (Permutation Coding Neural Classifier) and LIRA (Limited Receptive Area) neural classifiers. These neural classifiers are multipurpose neural classifiers. We applied them in micromechanics. Information about shape and texture of the micro workpiece can be used to improve precision of both assembly and manufacturing processes. The proposed neural classifiers were tested offline in the both tasks.
Keywords: Computer vision, neural network, shape recognition, texture recognition, micromechanics.
Resumen
Dos clasificadores neuronales fueron desarrollados para el reconocimiento de imágenes: PCNC (clasificador neuronal con codificación con permutaciones) y LIRA (clasificador neuronal con área de recepción limitada). Estos clasificadores neuronales son clasificadores de diferentes aplicaciones. Nosotros usamos ellos en micromecánica. La información sobre la forma y textura del micro objeto se puede utilizar para mejorar la precisión de los procesos de ensamble y de fabricación. Los redes neuronales propuestos fueron probados fuera de línea en ambos tareas.
]]> Palabras clave: Visión computacional, redes neuronales, reconocimiento de forma, reconocimiento de textura, micromecánica.
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Acknowledgment
This work was supported in part by projects CONACYT 50231, PAPIIT IN108606–3, PAPIIT IN116306–3.
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