Shashi Gowda
I am working as Associate Professor in the Department of Electronics and Communication Engineering, National Institute of Enginnering, Mysuru. I obtained my doctoral degree and M.Tech degree (VLSI Design and Embedded System) from Visvesvaraya Technological University, Belgaum and BE (Electronics and Communication) from Mangalore University. My area ofresearch is on On-Chip architecture design and implementation, ASIC implementation of Image processing techniques, TLM architecture and Verification Methodologies, Network on chip design and implementation, Biometric and Image processing. I am Life member of IETE and member of VLSI society of India.
less
InterestsView All (11)
Uploads
Papers
method. The overall designed system increases the efficiency. The Markov Chain Monte Carlo is customized for a given error tolerance as comparable to the requirement of the system. The developed hardware is verified for the functionality, as an authentication
for iris recognition as a biometric personal identification and verification. Human iris is unique and differs from one
individual to another. Just as finger prints, biomedical proves
human irises are distinct. Also, iris can be easily accessed from any visual capturing device. The two dimensional structure of iris further assists the technology. This paper describes the extraction of iris region from an image of the human eye. The proposed algorithm defines a new method to segment Iris from the image. It’s a new technique for circular edge detection particularly for Iris recognition. An image undergoes various operations like black and white conversion, edge detection and filtering. The fact that the intensity of iris lies between the intensities of pupil and rest of the eye is the key here to extract iris. A simple vertical and horizontal scan is done over the image to get the tangents of the circles. A mathematical analysis is done on the images to get the radius and the center of the circle and hence the inner and outer circles of the iris are drawn or Hough transform can be done using the obtained values for more accuracy. We are constructed the circles after obtaining the values
method. The overall designed system increases the efficiency. The Markov Chain Monte Carlo is customized for a given error tolerance as comparable to the requirement of the system. The developed hardware is verified for the functionality, as an authentication
for iris recognition as a biometric personal identification and verification. Human iris is unique and differs from one
individual to another. Just as finger prints, biomedical proves
human irises are distinct. Also, iris can be easily accessed from any visual capturing device. The two dimensional structure of iris further assists the technology. This paper describes the extraction of iris region from an image of the human eye. The proposed algorithm defines a new method to segment Iris from the image. It’s a new technique for circular edge detection particularly for Iris recognition. An image undergoes various operations like black and white conversion, edge detection and filtering. The fact that the intensity of iris lies between the intensities of pupil and rest of the eye is the key here to extract iris. A simple vertical and horizontal scan is done over the image to get the tangents of the circles. A mathematical analysis is done on the images to get the radius and the center of the circle and hence the inner and outer circles of the iris are drawn or Hough transform can be done using the obtained values for more accuracy. We are constructed the circles after obtaining the values