title: Higher order statistics in computer vision: analysis of images and detection of extraneous objects in images.
abstract: The aim of this work is to present methods for classifying images and locating extraneous objects within images. Our methods make use of higher order statistics, transforms of data into the frequency domain, and characteristics of the resulting clusters.
authors.affiliation: Department of Mathematics, Institute for Studies in Theoretical Physics and Mathematics, Tehran, Iran.
authors.forename: Ali
authors.initials: A
authors.lastname: Farhadi
authors.forename: Mehrdad
authors.initials: M
authors.lastname: Shahshahani
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D010781:Photography; D015203:Reproducibility of Results