Undoing the Affine Transformation Using Blind Source Separation

• Published in: Independent Component Analysis and Blind Signal Separation pp. 360 - 367
• Main Authors: Guney, Nazli, Ertuzun, Aysin
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2006; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Affine Transformation; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Independent Component Analysis; Information, signal and communications theory; Object Boundary; Object Recognition; Pattern recognition. Digital image processing. Computational geometry; Signal processing; Telecommunications and information theory; Time Structure; Invariant; Computer vision; Source separation; Image processing; Mixture theory; Blind source separation; Pattern recognition; Object recognition; Affine transformation; Blind separation; Size effect; Signal processing; Matching task; Pattern matching; Principal component analysis
• ISBN: 3540326308; 9783540326304
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11679363_45

Recognition of planar objects from their images taken from different viewpoints requires affine invariants calculated from the object boundaries. The equivalence between affine transformation and the source mixture model simplifies the recognition problem. The rotation, scaling, skewing, and translation effects of the affine transformation can be undone by using blind source separation (BSS) techniques to go back to a canonical object view. Then, the problem is reduced from a more involved affine invariant search to a simple shape matching task. Point correspondence between two curves initially related by an affine transformation is obtained with further processing.