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Jeyanthi, P.
- Texture Based Image Clustering Using Wavelets
Abstract Views :183 |
PDF Views:2
Authors
Affiliations
1 Department of Information Technology, Sathyabama University, Chennai, IN
2 Department of Electronics and Communication Engineering, Anna University, Chennai, IN
1 Department of Information Technology, Sathyabama University, Chennai, IN
2 Department of Electronics and Communication Engineering, Anna University, Chennai, IN
Source
Data Mining and Knowledge Engineering, Vol 3, No 15 (2011), Pagination: 922-926Abstract
Clustering is traditionally viewed as an unsupervised method for data analysis. The primary objective of cluster analysis is to partition a given data set into homogeneous clusters. In this paper, we present a novel algorithm for performing texture based clustering using wavelets. The approximation band of image Discrete Wavelet Transform is considered for segmentation which contains significant information of the input image. The Histogram based algorithm is used to obtain the number of regions and the initial parameters like mean, variance and mixing factor. The centroides are calculated and perform the clustering using k means. It is observed that the proposed method is computationally efficient than the k means algorithm and improved k means algorithm.Keywords
Cluster, Histogram, Segmentation, Wavelet.
- Medical Image Compression using Lossless and Lossy Systems by 3 Dimensional Haar Wavelet Transform
Abstract Views :123 |
PDF Views:0
Authors
Affiliations
1 Govt Arts College, Udumalpet - 642126, Tamil Nadu, IN
1 Govt Arts College, Udumalpet - 642126, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 48 (2016), Pagination:Abstract
Objectives: The advancement of digital structure human body images are created by Medical imaging. Compression of these images is hence needed for the images to be stored and transmitted. Compression of these images needs to be attained considerably, without compromising the image quality. Methods/Statistical Analysis: The most particular element of Haar Transform lies in the way that it lends itself effectively to fundamental manual estimations. It has been turned out to be an extremely constructive mechanism for image handling. The Haar convert reconverts a unique indication into Bi sub-level signals of quasi- its extent.3 Dimensional Haar Wavelet Transform (3 Dimensional HWT) is one of the computations which can moderate the estimation work in Haar Transform (HT) and Fast 3 Dimensional Haar Transform (3 Dimensional HT). Findings: The proposed work of 3 Dimensional HAAR WAVELET TRANSFORM (HWT) through parameterization cause to enhancement of efficiency in picture pressure with regards to unique choice of the wavelet and logarithmic DWT. Correlation between different lossy and lossless segments in 1−D image channels is investigated in this paper and a technique to make use of this redundancy is suggested. Application/Improvement: Any medical image compression application can adopt this technique and further improvements can be done on 3 Dimensional HAAR picture quality enhancement along with lossy compression.Keywords
(3 DimensionalHWT), 3 Dimensional Haar wavelet Transform, Image Compression, Lossless and Lossy Compression.Full Text
- Effect Of Nanosilica On Ethylene Propylene Diene Monomer Rubber Nanocomposites
Abstract Views :123 |
PDF Views:2
Authors
Source
International Journal of Innovative Research and Development, Vol 2, No 5 (2013), Pagination:Abstract
EPDM nanocomposites based on Nano-silica in combination with other inter fillers in were prepared and studied. Mechanical, Electrical, Thermal and Morphology Characterization of EPDM – Nano Composites were studied. Incorporation of nanofillers in EPDM rubber compound found to increase the thermal resistance of nanocomposites and decrease the electrical resistance properties.
Keywords
EPDM, Nano-silica, SEM –EDS, Thermal resistance, Volume resistivityFull Text