A study of automatic recognition and counting system of urine-sediment visual components

This paper discusses how to develop automatic recognition and count system for urine-sediment visual components. With the help of image processing technology, image segmentation, representation and description, geometric features and texture features have been extracted. The urine-sediment visual co...

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Hauptverfasser:	Xiaomou Zhou, Xingming Xiao, Chi Ma
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Accuracy Artificial neural networks Classification algorithms Feature extraction feature selection genetic algorithm image processing Image segmentation neural network Pattern recognition pattern recognization Visualization
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Beschreibung
Zusammenfassung:	This paper discusses how to develop automatic recognition and count system for urine-sediment visual components. With the help of image processing technology, image segmentation, representation and description, geometric features and texture features have been extracted. The urine-sediment visual components are categorized and counted through micro-image automatic recognition and count system with neural network classifier based on genetic algorithm.
ISSN:	1948-2914 1948-2922
DOI:	10.1109/BMEI.2010.5639648