Kernel principal component analysis for texture classification

IEEE Signal Processing Letters

Volumn 8, Issue 2, 2001, Pages 39-41

  Kim, K I ^a   Park, S H ^a   Kim, H J ^a  

^a Kyungpook National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

COLOR IMAGE PROCESSING; COMPUTATIONAL METHODS; CONFORMAL MAPPING; FEATURE EXTRACTION; LEARNING SYSTEMS; NONLINEAR SYSTEMS; POLYNOMIALS; PRINCIPAL COMPONENT ANALYSIS;

FEATURE SPACE; KERNEL PRINCIPAL COMPONENT ANALYSIS; NONLINEAR MAP; POLYNOMIAL KERNEL; TEXTURE CLASSIFICATION;

IMAGE ANALYSIS;

EID: 0035251844     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/97.895369     Document Type: Article

References (3)

1. S. Haykin, Neural Network - A Comprehensive Foundation, 2nd ed. Englewood Cliffs, NJ: Prentice Hall, 1999.
2. B. Schölkopf, A. Smola, and K. Müller, "Nonlinear component analysis as a kernel eigenvalue problem," Neural Comput., vol. 10, pp. 1299-1319, 1998.
3. T. Randen and J. H. Husoy, "Filtering for texture classification: A comparative study," IEEE Trans. Pattern Anal. Machine Intell., vol. 21, pp. 291-310, 1999.