Journal
INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING
Volume 12, Issue 6, Pages -Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0219691314500441
Keywords
Histogram; meaningful modes; scale-space; segmentation
Funding
- Department of Mathematics at UCLA
- NSF [DMS-0914856]
- UC Lab Fees Research
- Keck Foundation
- ONR [N00014-08-1-119, N00014-09-1-360]
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In this paper, we present an algorithm to automatically detect meaningful modes in a histogram. The proposed method is based on the behavior of local minima in a scale-space representation. We show that the detection of such meaningful modes is equivalent in a two classes clustering problem on the length of minima scale-space curves. The algorithm is easy to implement, fast and does not require any parameter. We present several results on histogram and spectrum segmentation, grayscale image segmentation and color image reduction.
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