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Brindha, R.
- Multiple Image Watermarking in DWT Domain Using Neural Network
Authors
1 Avinashilingam University for Women, Coimbatore, IN
Source
Digital Image Processing, Vol 1, No 1 (2009), Pagination: 16-20Abstract
This paper proposes the formulation of a more secure image watermarking methodology based on exploitation of the perpetual capacity of Discrete Wavelet Transforms (DWT) and reversible compression capability of Counter Propagation Neural network (CPN). The usefulness of CPN in mapping watermark images into few bits and subsequent embedding with the cover images in wavelet domain is demonstrated. The proposed method exhibits high security,high capacity and high imperceptibility features. Low embedding and tracking costs and low probability of coincidence are making this method unique among the previously investigated techniques by various researchers.Keywords
Image Watermarking, Counter Propagation Neural Network, DWT, Digital Watermarking, Cryptography, Image Mapping, Neural Network.
- Implementation of Protection and Accident Identification System for a Vehicle
Authors
1 Dept. Electronics and Communication Engineering, Sri Eshwar College of Engineering, Kinathukadavu, IN
Source
Automation and Autonomous Systems, Vol 6, No 2 (2014), Pagination: 58-62Abstract
Now-a-days most of the public owns a vehicle,meanwhile the theft is also happening. The safety of vehicles is extremely essential. Vehicle tracking and locking system installed in the vehicle, to track the place and locking engine motor. The place of the vehicle identified using Global Positioning system (GPS) and Global system mobile communication (GSM). These systems constantly watch a moving Vehicle and report the status on demand. When the theft identified, the responsible person send SMS to the microcontroller, then microcontroller issue the control signals to stop the engine motor. Authorized person need to send the password to controller to restart the vehicle and open the door. This is more secured, reliable and low cost.Keywords
Vehicle Tracking, Locking, Microcontroller, GPS, GSM.- An Enhanced Detection of White Matter Lesions in MRI Brain Images
Authors
1 Pollachi Institute of Engineering and Technology, Poosaripatti, IN
2 Pollachi Institute of Engineering and Technology, Poosaripatti, IN
Source
Biometrics and Bioinformatics, Vol 9, No 3 (2017), Pagination: 61-64Abstract
White Matter Lesions are small areas of dead cells found in the parts of the brain. In general it is difficult for medical experts accurately quantify the WMLs due to decreased contrast between White Matter (WM) and Grey Matter (GM) in MRI brain images. The main aim is to detect the White Matter Lesions present in MRI brain images which may result in memory loss or even death. This can be done by Fuzzy C-means Clustering (FCM) algorithm which is less sensitive to noise present at output and it detects false lesions also. To overcome this and to make detection more accurate Particle Swarm Optimization algorithm is used. PSO yields high sensitivity, specificity and overall accuracy over FCM.
- Drowsiness Detection Using Artificial Neural Network
Authors
1 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 12, No 5 (2020), Pagination: 99-103Abstract
When a driver doesn’t get proper rest, they fall asleep while driving and this leads to fatal accidents. This particular issue demands a solution in the form of a system that is capable of detecting drowsiness and to take necessary actions to avoid accidents.
The detection is achieved with three main steps, it begins with face detection and facial feature detection using the famous Viola Jones algorithm followed by eye tracking. By the use of correlation coefficient template matching, the eyes are tracked. Whether the driver is awake or asleep is identified by matching the extracted eye image with the externally fed template (open eyes and closed eyes) based on eyes opening and eyes closing, blinking is recognized. If the driver falling asleep state remains above a specific time (the threshold time) the vehicles stops and an alarm is activated by the use of a specific microcontroller, in this prototype an Arduino is used.