Work place: Department of Computer Science and Engineering, GITAM University, Visakhapatnam

E-mail: koka.jyothirmayi@gmail.com


Research Interests: Data Mining, Image Processing, Computer Architecture and Organization


T. Jyothirmayi is presently working as Assistant Professor in the department of Computer Science and Engineering, GIT, GITAM University, Visakhapatnam. She presented research papers in national and international conferences and journals of good repute. She guided several students for Project work in department of Computer Science Engineering. Her current research interests include image processing and data mining.

Author Articles
Performance Evaluation of Image Segmentation Method based on Doubly Truncated Generalized Laplace Mixture Model and Hierarchical Clustering

By T.Jyothirmayi K Srinivasa Rao P.Srinivasa Rao Ch.Satyanarayana

DOI: https://doi.org/10.5815/ijigsp.2017.01.06, Pub. Date: 8 Jan. 2017

The present paper aims at performance evaluation of Doubly Truncated Generalized Laplace Mixture Model and Hierarchical clustering (DTGLMM-H) for image analysis concerned to various practical applications like security, surveillance, medical diagnostics and other areas. Among the many algorithms designed and developed for image segmentation the dominance of Gaussian Mixture Model (GMM) has been predominant which has the major drawback of suiting to a particular kind of data. Therefore the present work aims at development of DTGLMM-H algorithm which can be suitable for wide variety of applications and data. Performance evaluation of the developed algorithm has been done through various measures like Probabilistic Rand index (PRI), Global Consistency Error (GCE) and Variation of Information (VOI). During the current work case studies for various different images having pixel intensities has been carried out and the obtained results indicate the superiority of the developed algorithm for improved image segmentation.

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