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• W1946346328 abstract "This paper proposes a real time system for deformable template based object detection and classification, to segment an object of interest from the stationary complex background. Polygonal templates were defined to characterize basic geometrical shapes, such as square and hexagon. The templates have the capability to deform its shape to fit the real object, The model is being fitted to the object using its edge information, which was extracted using Canny edge detection algorithm. The deformation of the model matched the object by maximizing likelihood probability density function. Likelihood energy is computed in each model position, dimension, and orientation. To limit the computation, detection of the object is performed by calculating its moment energy and defining searching areas. This will result in a faster processing time. The system's result is a description of the shape, size, and orientation of the objects." @default.
• W1946346328 created "2016-06-24" @default.
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• W1946346328 date "2002-11-27" @default.
• W1946346328 modified "2023-09-27" @default.
• W1946346328 title "Design and implementation of object detection and classification system based on deformable template algorithm" @default.
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• W1946346328 doi "https://doi.org/10.1109/apccas.1998.743755" @default.
• W1946346328 hasPublicationYear "2002" @default.
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