Work place: Department of Information Science and Engineering, SDMIT, Ujire, Karnataka, India
E-mail: dharmannasdmit@gmail.com
Website:
Research Interests: Embedded System, Computer Networks, Medical Image Computing
Biography
Dharmanna Lamani is currently HOD of information science and engineering, SDM Institute of technology, Ujire, Karnataka. He obtained M.Tech degree from VTU, Belagavi. He was awarded Ph.D. in computer science and engineering from VTU, Belagavi. His research interest includes Medical Image Processing, Embedded System design, Pattern Recognition and Computer Networking. He has published around 15 papers in reputed Journals and Conferences
By Chandrappa S Dharmanna Lamani Shubhada Vital Poojary Meghana N U
DOI: https://doi.org/10.5815/ijeme.2017.05.05, Pub. Date: 8 Sep. 2017
The Internet of Things (IoT) is a network of interconnected devices which are outfitted with sensors and Radio-Frequency Identification (RFID) devices. These devices are uniquely addressable and use standard communication protocols like Transmission Control Protocol (TCP), User Datagram Protocol (UDP) and Internet Control Message Protocol (ICMP) in a networking environment. Here devices are communicating with each other without human interaction. The objective of this work is to provide an Automatic Railway Gate Controller, which operates the railway gates without gatekeeper which makes it useful for operation at level crossings. This controller deals with the reduction of time of which the gate is being kept closed and provide the safety to the road users by reducing the accidents that usually occur due to carelessness of road users and the gatekeepers. In addition to this, one more additional module is implemented for the passenger’s convenience. Here, passenger needs to register their phone number via website to get destination arrival notification. This system is cost effective, real time and automatic.
[...] Read more.By Dharmanna Lamani T. C. Manjunath Mahesh M Y S Nijagunaraya
DOI: https://doi.org/10.5815/ijigsp.2015.07.02, Pub. Date: 8 Jun. 2015
Early identification of diabetic retinopathy is highly beneficial for preventing the progression of disease. Appearance of blood vessels & retinal surface is a good ophthalmological sign of diabetic retinopathy in fundus images. In this paper, a novel method involving two approaches has been proposed for diagnosis of diabetic retinopathy. The first approach deals with estimation of fractal dimension of lesions by applying power spectral fractal dimension algorithms. For healthy retinas, fractal dimensions are found to be in the range of 2.00 to 2.069, whereas for retinas with diabetic retinopathy, fractal dimensions exceed upper limit. In the second approach, Gray Level Co-occurrence Matrix method is used to analyze the extracted regions from healthy and diabetes affected fundus retinal images. Texture features such as entropy & contrast are computed for healthy and unhealthy regions. These texture features are compared with fractal dimensions. The authors observed positive correlation between entropy and fractal dimensions, whereas negative correlation with contrast and fractal dimensions. Detailed implementations of the proposed work are presented.
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