Adaptive preprocessing of scanned documents
MMACTEE'08 Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering
On Straight Line Segment Detection
Journal of Mathematical Imaging and Vision
Multiresolution histogram analysis for color reduction
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Automated approaches for analysis of multimodal MRI acquisitions in a study of cognitive aging
Computer Methods and Programs in Biomedicine
Saliency-Guided consistent color harmonization
CCIW'13 Proceedings of the 4th international conference on Computational Color Imaging
| Hi-index | 0.01 |
In this work, we propose a method to segment a 1-D histogram without a priori assumptions about the underlying density function. Our approach considers a rigorous definition of an admissible segmentation, avoiding over and under segmentation problems. A fast algorithm leading to such a segmentation is proposed. The approach is tested both with synthetic and real data. An application to the segmentation of written documents is also presented. We shall see that this application requires the detection of very small histogram modes, which can be accurately detected with the proposed method