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ICPR
2006
IEEE
16 years 4 months ago
Pores and Ridges: Fingerprint Matching Using Level 3 Features
Fingerprint friction ridge details are generally described in a hierarchical order at three levels, namely, Level 1 (pattern), Level 2 (minutiae points) and Level 3 (pores and rid...
Anil K. Jain, Meltem Demirkus, Yi Chen
170
Voted
ICPR
2008
IEEE
15 years 10 months ago
A similarity measure under Log-Euclidean metric for stereo matching
Stereo matching has been one of the most active areas in computer vision for decades. Many methods, ranging from similarity measures to local or global matching cost optimization ...
Quanquan Gu, Jie Zhou
117
Voted
ICRA
2002
IEEE
94views Robotics» more  ICRA 2002»
15 years 8 months ago
Weighted Range Sensor Matching Algorithms for Mobile Robot Displacement Estimation
This paper introduces a “weighted” matching algorithm to estimate a robot’s planar displacement by matching twodimensional range scans. The influence of each scan point on ...
Samuel T. Pfister, Kristopher L. Kriechbaum, Sterg...
137
Voted
CIAC
2000
Springer
118views Algorithms» more  CIAC 2000»
15 years 7 months ago
Speeding Up Pattern Matching by Text Compression
Abstract. Byte pair encoding (BPE) is a simple universal text compression scheme. Decompression is very fast and requires small work space. Moreover, it is easy to decompress an ar...
Yusuke Shibata, Takuya Kida, Shuichi Fukamachi, Ma...
ICASSP
2010
IEEE
15 years 3 months ago
Partial sequence matching using an Unbounded Dynamic Time Warping algorithm
Before the advent of Hidden Markov Models(HMM)-based speech recognition, many speech applications were built using pattern matching algorithms like the Dynamic Time Warping (DTW) ...
Xavier Anguera, Robert Macrae, Nuria Oliver