Pattern Recognition
A fast scheme for optimal thresholding using genetic algorithms
Signal Processing
Performance Evaluation of Some Clustering Algorithms and Validity Indices
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal multi-thresholding using a hybrid optimization approach
Pattern Recognition Letters
A multi-level thresholding approach using a hybrid optimal estimation algorithm
Pattern Recognition Letters
A novel image thresholding method based on Parzen window estimate
Pattern Recognition
A new criterion for automatic multilevel thresholding
IEEE Transactions on Image Processing
Efficient Optimal Multi-level Thresholding for Biofilm Image Segmentation
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
Sub-grid and spot detection in DNA microarray images using optimal multi-level thresholding
PRIB'10 Proceedings of the 5th IAPR international conference on Pattern recognition in bioinformatics
Image segmentation of biofilm structures using optimal multi-level thresholding
International Journal of Data Mining and Bioinformatics
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
Efficient trade-off between speed processing and accuracy in summarizing data streams
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Biological assessment of grid and spot detection in cDNA microarray images
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Applications of multilevel thresholding algorithms to transcriptomics data
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
A multi-level thresholding-based method to learn fuzzy membership functions from data warehouse
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
A new algorithm for finding enriched regions in ChIP-Seq data
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
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Optimal multilevel thresholding is a quite importantproblem in image segmentation and pattern recognition. Althoughefficient algorithms have been proposed recently, they do notaddress the issue of irregularly sampled histograms. Apolynomial-time algorithm for multilevel thresholding ofirregularly sampled histograms is proposed. The algorithm ispolynomial not just on the number of bins of the histogram,n , but also on the number of thresholds, k , i.e.it runs in θ (kn 2). The proposedalgorithm is general enough for a wide range of thresholding andclustering criteria, and has the capability of dealing withirregularly sampled histograms. This implies important consequenceson pattern recognition, since optimal clustering in theone-dimensional space can be obtained in polynomial time.Experiments on synthetic and real-life histograms show that fortypical cases, the proposed algorithm can find the optimalthresholds in a fraction of a second.