Title :
Metadata in Sequential Real-Time 2-D Detection
Author :
Vihonen, Juho ; Ala-Kleemola, Timo ; Jylhä, Juha ; Kerminen, Riitta ; Rauhamaa, Juhani ; Visa, Ari
Author_Institution :
Inst. of Signal Process., Tampere Univ. of Technol.
fDate :
6/1/2007 12:00:00 AM
Abstract :
Extraction of patterns is an important low-level operation in several vision applications. In particular, this work is motivated by the problem of detecting unknown vague structures in images with a minimum sample number. Tracing of an unknown structure is allowed by the spatial 2-D placement of extremum. Often, this permits near-optimum testing of hypothesis, which also accentuates the descriptive value of extrema. The proposed sequential approach guarantees predictable detection delay, which is a significant advantage in real-time use. The performance is demonstrated with simulations and real experiments, where transients have unknown starting time
Keywords :
feature extraction; image recognition; image sampling; image sequences; meta data; object detection; image detection; metadata; minimum sample number; near-optimum testing; pattern extraction; sequential real-time 2-D detection; Delay; Error probability; Image processing; Industrial relations; Sequential analysis; Signal processing; Signal processing algorithms; Stochastic resonance; Testing; Uncertainty; Extrema; image processing; sequential detection; shortest-path;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2006.888427