Quantitative evaluation of color image segmentation results
Pattern Recognition Letters
Multiresolution Color Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Color Space Selection for Biological Image Segmentation
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
The Colour Image Processing Handbook (Optoelectronics, Imaging and Sensing)
The Colour Image Processing Handbook (Optoelectronics, Imaging and Sensing)
Cell microscopic segmentation with spiking neuron networks
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
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Evaluation of segmentation is a non-trivial task and most often, is carried out by visual inspection for a qualitative validation. Until now, only a small number of objective and parameter-free criteria have been proposed to automatically assess the segmentation of color images. Moreover, existing criteria generally produce incorrect results on cytological images because they give an advantage to segmentations with a limited number of regions. Therefore, this paper suggests a new formulation based on two normalized terms which control the number of small regions and the color heterogeneity. This new criterion is applied to find an algorithm parameter to segment biological images.