Spatial Modification in the Parameters of Mountain Image Clustering Algorithm
Our proposed method used to overcome the drawbacks of computing values parameters in the mountain algorithm to image clustering. All existing clustering algorithms are required values of parameters to starting the clustering process such as these algorithms have a big problem in computing parameters. One of the famous clustering is a mountain algorithm that gives expected number of clusters, we presented in this paper a new modification of mountain clustering called Spatial Modification in the Parameters of Mountain Image Clustering Algorithm. This modification in the spatial information of image by taking a window mask for each center pixel value to compute distance between pixel and neighborhood for estimation the values of parameters σ, β that gives a potential optimum number of clusters requiring in image segmentation process. Our experiments show ability the proposed algorithm in image brain segmentation with a quality in the large data sets
Copyright (c) 2019 Al-Nahrain Journal for Engineering Sciences
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
- Each author retains the right to use the work for non-commercial purposes and for further research and spoken presentations.
- Each author retains the right to use the illustrations and research data in his/her future work.
- Only one offprint is provided free for each author. The authors can order offprints at the proof stage at certain rates depending on the number of additional copies required and the year of publication.
The publisher of the journal has all rights for publication in the paper, electronic and facsimile formats and for electronic capture, reproduction and licensing in all formats now and in perpetuity in the original and all derivative works.