Detail Stochastic Models for Capturing Image Variability   Oleh:  Srivastava, A. Jenis: Article from Bulletin/Magazine Dalam koleksi: IEEE Signal Processing Magazine vol. 19 no. 5 (2002), page 63-76. Topik: IMAGE; stochastic models; capturing image; variability Ketersediaan Perpustakaan Pusat (Semanggi) Nomor Panggil: SS26.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada     Lihat Detail Induk Isi artikel We review a result in modeling lower order (univariate and bivariate) probability densities of pixel values resulting from bandpass filtering of images. Assuming an object-based model for images, a parametric family of probabilities, called Bessel K forms, has been derived (Grenander and Srivastava 2001). This parametric family matches well with the observed histograms for a large variety of images (video, range, infrared, etc.) and filters (Gabor, Laplacian Gaussian, derivatives, etc). The Bessel parameters relate to certain characteristics of objects present in an image and provide fast tools either for object recognition directly or for an intermediate (pruning) step of a larger recognition system. Examples are presented to illustrate the estimation of Bessel forms and their applications in clutter classification and object recognition. Opini Anda Klik untuk menuliskan opini Anda tentang koleksi ini! Kembali

Copyright © 2006, 2007 Unika Atma Jaya, all rights reserved