A new approach for image segmentation using improved k-means and ROI saliency map. Issue 6 (18th August 2017)

• Record Type: Journal Article
• Authors: Sharma, Priyansh; Sharma, Mayank Satya Prakash; Tomar, Ranjeet Singh
• Is Part Of: Journal of information & optimization sciences. Volume 38:Issue 6(2017)
• Page Start: 927
• Page End: 935
• Publication Date: 2017-08-18
• Subjects: Real Image -- Region of Interest (ROI) -- K-means -- Mean -- Standard Deviation -- Entropy -- Accuracy; 68U10; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2017.1372138
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: The very crucial part of image processing system is Image Segmentation (IS). In the IS process, the accuracy is dependent on segmented image. In this paper, a new method for image segmentation is shown using improved K-means and region of interest (ROI) saliency map. The proposed system is classified the brain MRI and breast MRI pictures. In this process, detect the portion of tumor from MRI image. By the use of ROI saliency map algorithm, detect only circle section of the picture on the basis of connected component. The experimental dataset contains brain MRI and breast MRI images. The outcome is calculated on the mean (M), standard deviation (STD), entropy (E) and accuracy (ACC). This algorithm is matched with adaptive K means approach. The proposed algorithm gives enhanced outputs as compared to existing approach.