This paper proposes a novel system for face recognition which utilises the parametric eigenspace of Murase and Nayar (1993) to determine both the pose and identification of a face held within a current face database. In order that all views from profile to frontal are available for recognition a sample of views are taken from a range of angles so that, during the identification process, virtual views can be estimated from a novel view to supply ordered coordinates in the eigenvector subspace for the recognition algorithm. The method is demonstrated on a set of faces and results show that the technique is practical. The system is described in the context of a theoretical model of human face recognition which closely resembles that described in the literature

Face recognition using virtual parametric eigenspace signatures

The relationship between snake active contours and Kohonen networks in the scope of object boundary detection is discussed. It is shown that these algorithms share many common features and that they are special cases of a more general structure proposed, which provides a common framework for their study and enables the design of new iterative algorithms for boundary extraction. >

https://ieeexplore.ieee.org/iel2/3312/9944/00471863.pdf

A common framework for snakes and Kohonen networks

This paper introduces some basic definitions, notions and properties of multivalued morphology. Its application in moving object segmentation and tracking is demonstrated.

Multivalued Morphology and its Application in Moving Object Segmentation and Tracking

Invited Papers: Recent HDTV systems (M. Kunt). Polynomial methods in motion analysis (T.S. Huang). Motion compensated spatiotemporal Kalman filter (J.W. Woods, J. Kim). Artificial neural networks in pattern recognition and signal classification (C.H. Chen). Form and content issues in the abductive framework for recognition (B. Chandrasekaran, J. Josephson). Inverse SAR planetary imaging (M.R. Coble, D.C. Munson). Multispectral image processing (P.E. Trahanias, A.N. Venetsanopoulos). Image Coding I. Fractal transforms: complexity versus fidelity (D.M. Monro). Compatible HDTV coding using MDPCM and VQ (X. Song, Y. Neuvo). Image Coding II. Coding of motion compensated prediction error images by morphological segmentation (W. Li, M. Kunt). Perceptually based contrast enhancement algorithm (T.H. Yu, S.K. Mitra). Image Segmentation and Feature Extraction I. Restoration of incomplete contour images using Markov random fields (S. Urago et al.). Cooperation between edge detection and region growing: The problem of control (M. Salotti, C. Garbay). Image Coding III. Motion-compensated wavelet coding of color images using adaptive vector quantization (S. Yao, R.J. Clarke). A novel approach to data interpolation for image-data compression (F.G.B. deNatale et al.). Image Segmentation and Feature Extraction II. Expectation-driven segmentation: a pyramidal approach (A. Broggi, G. Destri). Image matching for underwater 3-D vision (J. Santos-Victor, J. Sentieiro). Image Filtering I. Identification of multichannel and multidimensional systems using cumulants: applicatioh to colour imagqs (Y. Zhang et al.). Contrast enhancement through multiresolution decomposition (J.M. Jolion). Neural Networks for Image Processing. 3-D reconstruction of line-like objects in trinocular vision (D. Mingyue, F.M. Wahl). Image compression by Hadamard transform and neural network spectrum extrapolation (E. Costamagna et al.). Image Filtering II. A simplified 2-D IIR digital filter and its application to image processing (T. Hinamoto, M. Muneyasu). 2-D subset averaged median filters (R. Suoranta, K.-P. Estola). Image Classification. Face identification and feature extraction using hidden Markov models (F. Samaria, F. Fallside). Imaging of vehicles with linear array (G. Jacovitti et al.). Applications of Image Processing. Optical image processing technique speeds up algorithms of computer graphics (Y.B. Karasik). Bistatic radar imaging in laboratory (J. Bertrand et al.). Image Classification and Applications. A structural approach in stereo vision (C. Di Roberto et al.). Associative reduction of dimensionality in image classification (D. Anguita et al.).

Image processing : theory and applications : proceedings of IPTA '93, San Remo, Italy, 14-16 June 1993

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Image processing : theory and applications : proceedings of IPTA '93, San Remo, Italy, 14-16 June 1993