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Volumn 84, Issue 3, 2004, Pages 445-452

Probability distribution of sub-pixel edge position

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COMPUTER SIMULATION; CORRELATION METHODS; GAUSSIAN NOISE (ELECTRONIC); IMAGE ANALYSIS; IMAGE QUALITY; INTERPOLATION; MATHEMATICAL MODELS; METHOD OF MOMENTS; PARAMETER ESTIMATION; PROBABILITY DISTRIBUTIONS; SIGNAL NOISE MEASUREMENT; WHITE NOISE;

EID: 0742267043     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2003.11.010     Document Type: Article
Times cited : (4)

References (16)
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    • A computational approach to edge detection
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    • (1986) IEEE Trans. Pattern Anal. Machine Intell. , vol.8 , Issue.6 , pp. 679-698
    • Canny, J.1
  • 3
    • 34250098710 scopus 로고
    • Using Canny's criteria to derive a recursively implemented optimal edge detector
    • Deriche R. Using Canny's criteria to derive a recursively implemented optimal edge detector. Int. J. Comput. Vision. 1(2):1987;167-187.
    • (1987) Int. J. Comput. Vision , vol.1 , Issue.2 , pp. 167-187
    • Deriche, R.1
  • 4
    • 0027576636 scopus 로고
    • A computational approach for corner and vertex detection
    • Deriche R., Giruadon G. A computational approach for corner and vertex detection. Internat. J. Comput. Vision. 10(2):1993;101-124.
    • (1993) Internat. J. Comput. Vision , vol.10 , Issue.2 , pp. 101-124
    • Deriche, R.1    Giruadon, G.2
  • 5
    • 0003426417 scopus 로고
    • A non-maxima suppression method for edge detection with sub-pixel accuracy
    • F. Devernay, A non-maxima suppression method for edge detection with sub-pixel accuracy, INRIA Sophia Antipolis Research Report No. 2724, 1995.
    • (1995) INRIA Sophia Antipolis Research Report No. 2724 , vol.2724
    • Devernay, F.1
  • 6
    • 0027540417 scopus 로고
    • Orthogonal moment operators for sub-pixel edge detection
    • Ghosal S., Mehrotra R. Orthogonal moment operators for sub-pixel edge detection. Pattern Recognition. 26(2):1993;295-306.
    • (1993) Pattern Recognition , vol.26 , Issue.2 , pp. 295-306
    • Ghosal, S.1    Mehrotra, R.2
  • 7
  • 10
    • 0019686128 scopus 로고
    • Line finding with sub-pixel precision
    • MacVicar-Whelan P.J., Binford T.O. Line finding with sub-pixel precision. Proc. SPIE. 281:1981;26-31.
    • (1981) Proc. SPIE , vol.281 , pp. 26-31
    • Macvicar-Whelan, P.J.1    Binford, T.O.2
  • 11
    • 0026205277 scopus 로고
    • Efficient method for finding the position of object boundaries to sub-pixel precision
    • Oakley J.P., Shann R.T. Efficient method for finding the position of object boundaries to sub-pixel precision. Image Vision Comput. 9(4):1991;272-272.
    • (1991) Image Vision Comput. , vol.9 , Issue.4 , pp. 272-272
    • Oakley, J.P.1    Shann, R.T.2
  • 13
    • 0034301478 scopus 로고    scopus 로고
    • Sub-pixel localisation of edges with non-uniform blurring: A finite closed-form approach
    • Shan Y., Boon G.W. Sub-pixel localisation of edges with non-uniform blurring. a finite closed-form approach Image Vision Comput. 18(13):2000;1015-1023.
    • (2000) Image Vision Comput. , vol.18 , Issue.13 , pp. 1015-1023
    • Shan, Y.1    Boon, G.W.2
  • 14
    • 0005097520 scopus 로고    scopus 로고
    • Analytical and empirical performance evaluation of sub-pixel line and edge detection
    • K.W. Bowyer, & P.J. Phillips. IEEE Computer Society Press
    • Steger C. Analytical and empirical performance evaluation of sub-pixel line and edge detection. Bowyer K.W., Phillips P.J. Empirical Evaluation Methods in Computer Vision. 1998;188-210 IEEE Computer Society Press.
    • (1998) Empirical Evaluation Methods in Computer Vision , pp. 188-210
    • Steger, C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.