Published June 1994
by Society of Photo Optical .
Written in English
|The Physical Object|
Get this from a library! Image algebra and morphological image processing II: July , San Diego, California. [Paul D Gader; Edward R Dougherty; Society of Photo-optical Instrumentation Engineers.; SPIE Digital Library.;]. Get this from a library! Image algebra and morphological image processing: July , San Diego, California. [Paul D Gader; Society of . Image Algebra and Morphological Image Processing IV Article (PDF Available) in Proceedings of SPIE - The International Society for Optical Engineering . Generalized image algebra operations are used to obtain fuzzy morphological or linear operation. The parameters for the generalized operations are learned in a fashion similar to standard backpropagation, but with training rules based on a combination of stochastic learning and gradient descent techniques.
Image Processing and Mathematical Morphology: Fundamentals and Applications is a comprehensive, wide-ranging overview of morphological mechanisms and techniques and their relation to image processing. More than merely a tutorial on vital technical information, the book places this knowledge into a theoretical framework. Vincent, Luc.: “Fast Opening Functions and Morphological Granulometries” In SPIE Image Algebra and Morphological Image Processing V, Vol pp. . COMPUTER VISION, GRAPHICS, AND IMAGE PROCESS () Image Algebra: An Overview G. X. RITTER, J. N. WILSON, AND J. L. DAVIDSON Center for Computer Vision Research, Department of Computer and Injormation Sciences, University of Florida, Gainesville, Florida I Received J; revised Ap This paper is the first in a sequence of . This paper states and proves a number of properties of the tophat and the tophat spectrum. These include: the tophat is antiextensive and idempotent (but not increasing); each image in the tophat spectrum is size-limited and open; the structuring element family need not be mutually open to generate a tophat spectrum; if the SE family is mutually open, and the original image is binary, each.
Image algebra and morphological image processing III. Bellingham, Wash.: SPIE, © (DLC) (OCoLC) Material Type: Conference publication, Document, Internet resource: Document Type: Internet Resource, Computer File: All Authors / Contributors: Paul D Gader; Edward R Dougherty; Society of Photo-optical Instrumentation Engineers. Contact & Support +1 (United States) +1 (International) Hours: am to pm PST. Help | Contact Us. Figure 2 Behavior of the generalized hit-or-miss operation. Peaks of A eB occur at locations for which the HIT template fits under the curve and the MISS template fits above the curve /SPIE Vol. Network Structure The image algebra network is composed of two parts: a feature extraction network followed by the feedforward network. A neural network structure that learns feature extraction and classification operations simultaneously is described. The feature extraction operations are represented using generalized image algebra operations. Learning rules are described. Linear operations and nonlinear, hit-or-miss operations are used to perform handwritten digit recognition.