Journal
INTERNATIONAL JOURNAL OF COMPUTER VISION
Volume 85, Issue 2, Pages 167-181Publisher
SPRINGER
DOI: 10.1007/s11263-009-0251-z
Keywords
Computer vision; Image segmentation; Quantitative evaluation; Boundary matching
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We present a thorough quantitative evaluation of four image segmentation algorithms on images from the Berkeley Segmentation Database. The algorithms are evaluated using an efficient algorithm for computing precision and recall with regard to human ground-truth boundaries. We test each segmentation method over a representative set of input parameters, and present tuning curves that fully characterize algorithm performance over the complete image database. We complement the evaluation on the BSD with segmentation results on synthetic images. The results reported here provide a useful benchmark for current and future research efforts in image segmentation.
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