Annotation and Retrieval of Cell Images
نویسندگان
چکیده
A multi-net neural computing system is described that can be used for classifying images based on intrinsic image features and extrinsic collateral linguistic description of the contents. A novel representation scheme based on wavelet analysis of images and a subsequent Zernike moment computation helps in a systematic extraction of image features; collateral linguistic description are obtained by the automatic extraction of single and compound keywords. We give a formal description of the system using the Z formal specification notation. An image data set comprising 480 fluorescent stained images of lymphocytes was used in the test of a 3-component unsupervised multi-net neural computing system. The classification accuracy of this system was found to be just over 85%.
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