文章基本信息

标题：An Analytical Study on Image Parsing
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作者：Anurag Kumar Mishra ; Dr.Sipi Dubey
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2012
卷号：2
期号：8
出版社：S.S. Mishra
摘要：Image parsing is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. For instance, for a database of horse images, image parsing can be thought of as the task of classifying each pixel as part of a horse or non horse. In more complicated problems, image parsing might require multiple labels, e.g. roads, cars, houses etc. in outdoors scenes. Clearly, pixels cann ot be classified in this manner based only on their intensities or even local feature descriptors. Contextual information plays a critical role in Resolving ambiguities. Image parsing can be posed as a supervised learning problem where a classifier is learnt from training data consisting of images and corresponding label maps. Auto context and convolution networks are two promising approaches that apply context to image parsing in the supervised learning setting. Convolution networks are a type of artificia l neural network (ANN) in which each processing element carries out a convolution followed by nonlinearity.
关键词：Query By Image Content; Chabot; ImageParser