Development Of Position Feedback Sensor Based On Vision Using Neural Network

dc.contributor.author	Mohd Yunos, Yushazaziah
dc.date.accessioned	2018-08-23T01:49:13Z
dc.date.available	2018-08-23T01:49:13Z
dc.date.issued	2009-12
dc.description.abstract	Measurement of linear position is fundamental in many industrial processes especially as positioning feedback. Optical encoder is one of the frequently used position sensor. Unfortunately, there are some disadvantages in the usage of this type of encoder. This proposed work presents an approach to build a position sensor using image classification. The image was classified by using supervised backpropagation neural network. Input image that was fed to the classifier is a grayscale image of the surrounding environment (up view) which was captured to represent the position. The features in the image are not clear and thus feature extraction is difficult to be performed to extract statistical data. The image was rescaled and fed into the network as one vector. Series of images were captured at various positions with each series having different distance to each other. As the interval between images becomes closer, there is more overlapping between images.	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/6383
dc.language.iso	en	en_US
dc.publisher	Universiti Sains Malaysia	en_US
dc.subject	Position Feedback Sensor	en_US
dc.subject	Vision Using Neural Network	en_US
dc.title	Development Of Position Feedback Sensor Based On Vision Using Neural Network	en_US
dc.type	Thesis	en_US

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