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  Exudates Detection of Retinal Images using Otsu’s Thresholding and Kirsch’s Templates  
  Authors : Shreyasi Hazra; Atashi Patra; Tuhin Utsab Paul
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Ophthalmic diseases like diabetic retinopathy, macular degeneration, glaucoma, etc. may cause gradual loss of eyesight and are some of the reasons behind blindness. Hence, blood vessel assessment and segmentation play a key role in the diagnosis of retinal disorders. The manual detection of narrow blood vessels of retinal images is time consuming and may result in erroneous output. Therefore, computer aided, robust and performance oriented algorithm is required to detect and segment the blood vessels efficiently. The present work proposes an algorithm that uses thresholding technique, basic morphological operations and Kirsch’s edge detection operator to detect the blood vessels and segment the hard exudates efficiently. The detected exudates regions are then compared with the ground truth exudate regions. Based on the correctly identified exudate regions between these two images, different performance parameters like accuracy, specificity, sensitivity, PPV, PLR and misclassified proportions have been measured to evaluate overall performance of the proposed algorithm. This algorithm successfully detects exudates with an average of 98.47% accuracy, 54.67% sensitivity, 99.82% specificity, 88.62% PPV, 303.73 PLR and 0.17% misclassified proportions.


Published In : IJCSN Journal Volume 5, Issue 4

Date of Publication : August 2016

Pages : 615-621

Figures :03

Tables : 02


Shreyasi Hazra : received her B. Tech degree in Electronics and Communication Engineering from JIS College of Engineering under West Bengal University of Technology in 2012. She has worked with IBM as Application Developer for 1 year and 8 months. Currently, she is pursuing her M.Tech in Electronics and Communication from Institute of Engineering & Management under same university. Her area of interest includes image processing & analysis.

Atashi Patra : has completed her B. Tech in Electronics and Communication Engineering from Asansol Engineering College under West Bengal University of Technology in 2013. Currently, she is pursuing her M.Tech in Electronics and Communication from Institute of Engineering & Management under same university. Her area of interest is in image processing & analysis.

Tuhin Utsab Paul : did his undergraduate and postgraduate degrees in computer science and engineering from the University of Calcutta. He is working as an assistant professor in the department of electronics and communication at the Institute of Engineering and Management since 2012. His research area includes bio – medical image processing, digital signal processing and embedded system design.








Security, DBSCAN, Outsourced Databases, Encryption

This paper presents various existing methods from different papers used for the privacy preserving query processing in data mining and over encrypted data can mention as (PPDM). To protect user data privacy, with the discussion of various proposals of privacy-preserving classification techniques are presented over the past papers. The existing techniques are applicable to outsourced database environments where the data resides in encrypted form on a third-party server and also the classification or clustering of the data with proper label is discussed here This paper proposed a new privacypreserving clustering protocol DBSCAN is used over encrypted data of the cloud. This protocol protects the confidentiality of the data, as a user’s input query, and hides the data access patterns. As well as provide fast access to data as better clustering is done using DBSCAN algorithm.


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