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Manish, T. I.
- Performance Evaluation of Face Recognition Using Gabor Filter, Log Gabor filter and Discrete Wavelet Transform
Abstract Views :248 |
PDF Views:186
Authors
D. Murugan
1,
S. Arumugam
2,
K. RajalakshmiDepartment of CSE, Francis Xavier Engineering College
3,
T. I. Manish
1
Affiliations
1 Department of CSE, Manonmaniam Sundaranar University, IN
2 Nandha College of Engineering and Technology, Erode, IN
3 Department of CSE, Francis Xavier Engineering College, IN
1 Department of CSE, Manonmaniam Sundaranar University, IN
2 Nandha College of Engineering and Technology, Erode, IN
3 Department of CSE, Francis Xavier Engineering College, IN
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 2, No 1 (2010), Pagination: 125-133Abstract
The face recognition problem is made difficult by the great variability in head rotation and tilt, lighting intensity and angle, facial expression, aging, partial occlusion (e.g. Wearing Hats, scarves, glasses etc.), etc. The Eigenfaces algorithm has long been a mainstay in the field of face recognition and the face space has high dimension. Principal components from the face space are used for face recognition to reduce dimensionality. A multiscale representation for face recognition is done to preserve the discriminant information prior to dimensionality reduction. In this paper, three multiscale representation techniques Gabor filter; Log Gabor filter and Discrete Wavelet Transform are applied prior to dimensionality reduction. PCA is then applied on the above techniques to find the face recognition accuracy rate and to compare the results of the three methods with PCA method. The approximation coefficients in discrete wavelet transform is extracted and it is used to compute the face recognition accuracy instead of using all the coefficients.Keywords
Eigenfaces, Face Space, Gabor Filter, Principal Components, Multiscale, Log Gabor Filter.Full Text
- A Comparative Analysis on Various Noise Reduction Techniques Tested for Medical Images
Abstract Views :292 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science & Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, IN
2 Department of Computer Science & Engineering, Adi Shankara Institute of Engineering & Technology, Ernakulam, Kerala, IN
1 Department of Computer Science & Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, IN
2 Department of Computer Science & Engineering, Adi Shankara Institute of Engineering & Technology, Ernakulam, Kerala, IN
Source
Journal of Network and Information Security, Vol 6, No 1 (2018), Pagination: 18-23Abstract
Noise removing in the medical image is still a challenging task in the research field especially for the imaging devices like mammogram and ultra-sound. Even though advance scanning technology has been invented, these conventional devices play a vital role in scanning the mammogram breast cancer and fetus images. During the image acquisition itself, these images will get corrupted by the physical interference which appears as a noise in an image and affects its visual quality. In this paper we have applied the various traditional and conventional mean based noise removal techniques for the impulse noise corrupted mammogram breast image and standard benchmark. From this comparative analysis we have found that alpha-trimmed mean filters gives the better result than the other filters in terms of PSNR, SSIM and visual quality.Keywords
Impulse Noise, Wiener Filter, Noise Reduction, Arithmetic Mean Filter, Medical Image.
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