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ICAPR
2009
Springer
15 years 10 months ago
Color Image Retrieval Using M-Band Wavelet Transform Based Color-Texture Feature
—Feature Extraction algorithm is a very important component of any retrieval scheme. We propose M-band Wavelet Transform based feature extraction algorithm in this paper. The MxM...
Malay Kumar Kundu, Priyank Bagrecha
ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
15 years 8 months ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
Qi Tian, Ying Wu, Thomas S. Huang
128
Voted
SMI
2008
IEEE
181views Image Analysis» more  SMI 2008»
15 years 10 months ago
SHREC - 08 entry: Local 2D visual features for CAD Model retrieval
A local shape feature has an advantage in dealing with deformable or articulated 3D models. We evaluate the performance of our local, 2D visual features and their integration meth...
Kunio Osada, Takahiko Furuya, Ryutarou Ohbuchi
SIGMOD
2010
ACM
324views Database» more  SIGMOD 2010»
15 years 8 months ago
Similarity search and locality sensitive hashing using ternary content addressable memories
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
Rajendra Shinde, Ashish Goel, Pankaj Gupta, Debojy...
COOPIS
2004
IEEE
15 years 7 months ago
Ontology for Nature-Scene Image Retrieval
This paper presents a framework for building an ontology to provide semantic interpretations in image contents. The novelty of this framework comes from building a MPEG-7 ontology ...
Song Liu, Liang-Tien Chia, Syin Chan