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Sampoornam, K. P.
- Complex Wavelet Transform Based Adaptive Multiple Watermarking Algorithm for Images
Abstract Views :160 |
PDF Views:3
Authors
Affiliations
1 Department of EEE, Kongu Engineering College, Perundurai, Erode-638 052, Tamil Nadu, IN
2 Department of ECE, JJ College of Engineering and Technology, Ammapettai, Tiruchirappalli - 620 009, Tamil Nadu, IN
3 Department of ECE, K.S.R.College of Engineering, Tiruchengode-637 215, TamilNadu, IN
1 Department of EEE, Kongu Engineering College, Perundurai, Erode-638 052, Tamil Nadu, IN
2 Department of ECE, JJ College of Engineering and Technology, Ammapettai, Tiruchirappalli - 620 009, Tamil Nadu, IN
3 Department of ECE, K.S.R.College of Engineering, Tiruchengode-637 215, TamilNadu, IN
Source
Digital Image Processing, Vol 3, No 5 (2011), Pagination: 305-308Abstract
In this paper, we present a novel multiple watermarking algorithm using Dual Tree Complex Wavelet Transform (DTCWT). CWT has more applicability in image transformation due to its excellence in directionality, oscillations, shift invariance and aliasing. Eigen values of mid frequency band of cover image are modified by Eigen values of dual binary watermarks, which are obtained by Singular Value Decomposition (SVD). Experimental results show that the proposed watermarking algorithm based on CWT is well suited for various gray scale images when compared to conventional DWT.Keywords
CWT, DWT, SVD and Multiple Watermarking.
- Drowsy Driver Alert System Using Image Processing
Abstract Views :173 |
PDF Views:3
Authors
Affiliations
1 Bannari Amman Institute of Technology, Sathyamangalam, TN, IN
2 Bannari Amman Institute of Technology, Sathyamangalam, TN, IN
1 Bannari Amman Institute of Technology, Sathyamangalam, TN, IN
2 Bannari Amman Institute of Technology, Sathyamangalam, TN, IN
Source
Digital Image Processing, Vol 9, No 7 (2017), Pagination: 153-156Abstract
A non-intrusive machine vision based concept is adopted in the development of Drowsy Driver Alert System. The system uses a small monochrome security camera that points directly towards the driver's face and monitors the driver's eyes in order to detect fatigue. The aim of this work is to develop a prototype drowsiness detection system. This paper describes about how to monitor the eye and detect for the eye closure. The system deals with information obtained for the binary version of the image to find the edges of the face, which narrows the area of where the eyes may exist. By considering the fact that the eye regions in the face reflect greater intensity changes than other parts, the eyes are located by finding the significant intensity changes in the face. The intensity changes in the eyes area determine whether eyes are open or closed. If the eyes are found closed for five consecutive frames, the driver is falling asleep and issues a warning signal.Keywords
Drowsiness Detection, Feature Extraction, Frame, Image Segmentation, Non-Invasive System.References
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