Abstract
In this paper, we introduce a region-based image retrieval system, FRIP. This system includes a robust image segmentation scheme using scaled & shifted color and shape description scheme using Modified Radius-based Signature. For image segmentation, by using our proposed circular filter, we can keep the boundary of object naturally and merge small senseless regions of object into a whole body. For efficient shape description, we extract 5 features from each region: color, texture, scale, location, and shape. From these features, we calculate the similarity distance between the query and database regions and it returns the top K-nearest neighbor regions.
| Original language | English |
|---|---|
| Pages (from-to) | 283-286 |
| Number of pages | 4 |
| Journal | Proceedings-International Conference on Pattern Recognition |
| Volume | 15 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2000 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
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Region-based image retrieval system using efficient feature description. / Ko, Byoung Chul; Lee, Hae Sung; Byun, Hyeran.
In: Proceedings-International Conference on Pattern Recognition, Vol. 15, No. 4, 01.01.2000, p. 283-286.Research output: Contribution to journal › Article
TY - JOUR
T1 - Region-based image retrieval system using efficient feature description
AU - Ko, Byoung Chul
AU - Lee, Hae Sung
AU - Byun, Hyeran
PY - 2000/1/1
Y1 - 2000/1/1
N2 - In this paper, we introduce a region-based image retrieval system, FRIP. This system includes a robust image segmentation scheme using scaled & shifted color and shape description scheme using Modified Radius-based Signature. For image segmentation, by using our proposed circular filter, we can keep the boundary of object naturally and merge small senseless regions of object into a whole body. For efficient shape description, we extract 5 features from each region: color, texture, scale, location, and shape. From these features, we calculate the similarity distance between the query and database regions and it returns the top K-nearest neighbor regions.
AB - In this paper, we introduce a region-based image retrieval system, FRIP. This system includes a robust image segmentation scheme using scaled & shifted color and shape description scheme using Modified Radius-based Signature. For image segmentation, by using our proposed circular filter, we can keep the boundary of object naturally and merge small senseless regions of object into a whole body. For efficient shape description, we extract 5 features from each region: color, texture, scale, location, and shape. From these features, we calculate the similarity distance between the query and database regions and it returns the top K-nearest neighbor regions.
UR - http://www.scopus.com/inward/record.url?scp=0000733419&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0000733419&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2000.902914
DO - 10.1109/ICPR.2000.902914
M3 - Article
VL - 15
SP - 283
EP - 286
JO - Proceedings - International Conference on Pattern Recognition
JF - Proceedings - International Conference on Pattern Recognition
SN - 1051-4651
IS - 4
ER -