DocumentCode
3033675
Title
New robust image operators and applications in automatic facial feature analysis
Author
Nguyen, Thang ; Huang, Thomas
Author_Institution
Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
Volume
3
fYear
1995
fDate
23-26 Oct 1995
Firstpage
524
Abstract
This paper discusses a collection of image operators we originally developed for automatic analysis of face images, but they can also be applied to many other image domains. Most of these are new operators, a few are enhanced variants: two region segmentation algorithms (edge-based and intensity-based), two feature detectors (a hybrid morphological-Laplacian, and an oriented morphological edge detector), a thin edge detector by morphological gradient with statistical thresholding, and a nonlinear smoothing filter (micro-clustering). These new operators were designed with specific criteria for maximum efficiency in automatic image analysis. Morphological, statistical, linear and nonlinear operators were extensively tested and combined to get the desired properties
Keywords
edge detection; face recognition; feature extraction; image recognition; mathematical morphology; nonlinear filters; smoothing methods; statistical analysis; automatic analysis; automatic facial feature analysis; automatic image analysis; edge based segmentation; face images; feature detectors; hybrid morphological Laplacian detector; image domains; intensity based segmentation; linear operator; microclustering; morphological gradient; morphological operator; nonlinear operator; nonlinear smoothing filter; oriented morphological edge detector; region segmentation algorithms; robust image operators; statistical operator; statistical thresholding; thin edge detector; Computer vision; Detectors; Face detection; Filters; Image analysis; Image edge detection; Image segmentation; Robustness; Smoothing methods; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1995. Proceedings., International Conference on
Conference_Location
Washington, DC
Print_ISBN
0-8186-7310-9
Type
conf
DOI
10.1109/ICIP.1995.537687
Filename
537687
Link To Document