2026-09-19T12:34:33Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/168632026-06-06T01:04:59Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Pawan Sinha.
Thoresz, Keith John, 1972-
Massachusetts Institute of Technology. Dept. of Brain and Cognitive Sciences.
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
2005-05-19T15:04:03Z
2005-05-19T15:04:03Z
2002
2002
http://hdl.handle.net/1721.1/16863
51639438
Thesis (S.M. in Computational Neuroscience)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2002.
Includes bibliographical references (p. 75-80).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
This thesis describes a representation for objects and scenes that is stable against variations in image intensity caused by illumination changes and tolerant to image degradations such as sensor noise. The representation, called a ratio-template, uses low-resolution ordinal contrast relationships as its matching primitives. The choice of these primitives was inspired not only by considerations of computational simplicity and robustness, but also by current knowledge of the early stages of visual processing in the primate brain. The resulting representation is biologically plausible, although there is currently no evidence to suggest that the representation is actually used by the primate visual system. Constructed manually at first, the ratio-template can be learned automatically from a set of examples. Two applications--face detection and scene indexing--are described. The ratio-template achieves detection rates higher than 90% and can process a 320×280 pixel image in 2.6 seconds at multiple scales.
by Keith John Thoresz.
S.M. in Computational Neuroscience
80 p.
1927702 bytes
1927437 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Brain and Cognitive Sciences.
Qualitative representation for recognition
Thesis
application/pdf
Publication
unknown
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