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82 Chapter 2 ■ Edge-Detection Techniques

et2_9.pgm ET2 with noise mean = 9
et3.pgm Edge test image, upper-left to lower-right boundary
et3_18.pgm ET3 with noise mean = 18

et3_3.pgm ET3 with noise mean = 3
et3_9.pgm ET4 with noise mean = 9
et4.pgm Edge test image, EF1.line at boundary

et4_18.pgm ET4 with noise mean = 18
et4_3.pgm ET4 with noise mean = 3
et4_9.pgm ET4 with noise mean = 9
et5.pgm Edge test image, ET1 2-pixel line at boundary

et5_18.pgm ET5 with noise mean = 18
et5_3.pgm ET5 with noise mean = 3
et5_9.pgm ET5 with noise mean = 9

n20b.pgm Noise in a black region
n20w.pgm Noise in a white region
wood.pgm Teak wood grain image (2.2a)
et1.edg Ground truth for ET1.PGM

et2.edg Ground truth for ET2.PGM
et3.edg Ground truth for ET3.PGM
et4.edg Ground truth for ET4.PGM

et5.edg Ground truth for ET5.PGM

2.12 References

Abdou, I. E. and Pratt, W. K. ‘‘Quantitative Design and Evaluation of Enhance-
ment/Thresholding Edge Detectors.’’ Proceedings of the IEEE 67 (1979):
753–763.
Baker, S. and Nayar, S. K. ‘‘Global Measures of Coherence for Edge Detector
Evaluation.’’ Proceedings of CVPR99 (2002): 373–379.
Basu, M. ‘‘Gaussian-Based Edge-Detection Methods: A Survey.’’ SMC-C 32
(August 2002): 252–260.