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Volumn , Issue , 2004, Pages 96-99

Interactive color image segmentation by region growing combined with image enhancement based on bezier model

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; IMAGE ANALYSIS; IMAGE ENHANCEMENT; IMAGE SEGMENTATION; INTERACTIVE COMPUTER SYSTEMS; PROBLEM SOLVING; VECTOR QUANTIZATION;

EID: 17044374285     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (12)

References (11)
  • 2
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    • Global color image segmentation strategies: Euclidean distance vs. vector angle
    • IEEE Press, Piscataway, NJ
    • S.Wesolkowski, Global Color Image Segmentation Strategies: Euclidean Distance vs. Vector Angle, Neural Networks for Signal Processing IX, IEEE Press, Piscataway, NJ, 1999, pp. 419-428.
    • (1999) Neural Networks for Signal Processing IX , pp. 419-428
    • Wesolkowski, S.1
  • 3
    • 84998577514 scopus 로고
    • Color image segmentation by a watershed algorithm and region adjacency graph processing
    • Nov.
    • Kari Saarinen, Color Image Segmentation by a Watershed Algorithm and Region Adjacency Graph Processing, IEEE Trans. on Image Processing, vol. 3, pp. 1021-1025, Nov. 1994.
    • (1994) IEEE Trans. on Image Processing , vol.3 , pp. 1021-1025
    • Saarinen, K.1
  • 4
    • 0141954042 scopus 로고    scopus 로고
    • T region-growing approach to color segmentation using 3D clustering and relaxation labeling
    • Aug.
    • Cheng, SC.,T Region-growing approach to color segmentation using 3D clustering and relaxation labeling, IEEE Trans. Image and Signal Processing, vol. 150, pp. 270-276, Aug. 2003.
    • (2003) IEEE Trans. Image and Signal Processing , vol.150 , pp. 270-276
    • Cheng, S.C.1
  • 5
    • 0032728722 scopus 로고    scopus 로고
    • Evolutionary segmentation of texture image using genetic algorithms towards automatic decision of optimum number of segmentation areas
    • M. Yoshimura and S.oe, Evolutionary segmentation of texture image using genetic algorithms towards automatic decision of optimum number of segmentation areas, Pattern Recognition, vol. 32, pp. 2041-2054, 1999.
    • (1999) Pattern Recognition , vol.32 , pp. 2041-2054
    • Yoshimura, M.1    Oe, S.2
  • 6
    • 0031189783 scopus 로고    scopus 로고
    • A region growing and merging algorithm to color segmentation
    • A. Tremeau, and N. Borel, A Region Growing and Merging Algorithm to Color Segmentation, Pattern Recognition, vol. 30, no. 7, pp. 1191-1203, 1997.
    • (1997) Pattern Recognition , vol.30 , Issue.7 , pp. 1191-1203
    • Tremeau, A.1    Borel, N.2
  • 8
    • 0031252183 scopus 로고    scopus 로고
    • An improved seeded region growing algorithm
    • Mehnert, An improved seeded region growing algorithm, Pattern Recognition Letters, vol. 18, pp. 1065-1071, 1997.
    • (1997) Pattern Recognition Letters , vol.18 , pp. 1065-1071
    • Mehnert1
  • 10
    • 0034444673 scopus 로고    scopus 로고
    • Unsupervised seed determination for a region-based color image segmentation scheme
    • Vancouver, Canada
    • N. Ikonomakis, Unsupervised Seed Determination For A Region-Based Color Image Segmentation Scheme, IEEE International Conference on Image Processing, Vancouver, Canada, 2000.
    • (2000) IEEE International Conference on Image Processing
    • Ikonomakis, N.1
  • 11
    • 15744398736 scopus 로고    scopus 로고
    • Interactive image segmentation using multiple color spaces
    • Wei Bao-gang, Li Xiangyang, Lu Dongming, Pan Yunhe, Interactive Image Segmentation Using Multiple Color Spaces, Computer Science, 24(7), pp.770-775, 2001
    • (2001) Computer Science , vol.24 , Issue.7 , pp. 770-775
    • Wei, B.-G.1    Li, X.2    Lu, D.3    Pan, Y.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.