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Subbiah Bharathi, V.
- An Efficient Method for Digital Imaging of Ancient Stone Inscriptions
Abstract Views :260 |
PDF Views:97
Authors
Affiliations
1 Department of CSE, Anna University, Chennai 600 025, IN
2 Easwari Engineering College, Ramapuram, Chennai 600 089, IN
1 Department of CSE, Anna University, Chennai 600 025, IN
2 Easwari Engineering College, Ramapuram, Chennai 600 089, IN
Source
Current Science, Vol 110, No 2 (2016), Pagination: 245-250Abstract
Ancient stone inscription is one of the most important primary sources to know about our ancient world such as age, art, politics, religion, medicine, etc. Image acquisition is the first stage for digitizing and preserving the stone inscriptions for further reference. The traditional method of wet paper squeezes is still being used, that will be digitized and preserved for recognition. In this communication, we propose a novel image acquisition method called Shadow photometric stereo method for upgrading the image for recognition. The efficiency of the proposed acquisition method has been proved in image thinning process. Improving the thinning quality of the characters facilitates better feature extraction for character recognition. An experiment has been performed on two stone inscriptions that were in different places, one placed inside laboratory and other in its original place, i.e. outside the laboratory. Analyses were performed in terms of performance measures such as hamming distance and peak signal-to-noise ratio. Comparisons with the best available results are given in order to illustrate the best possible technique that can be used as a powerful image acquisition method.Keywords
Ancient Stone Inscriptions, Image Processing, Shadow Photometric Stereo Method, Thinning Algorithms.Full Text
- Classification of CT Liver Images Using Local Binary Pattern with Legendre Moments
Abstract Views :284 |
PDF Views:96
Authors
Affiliations
1 Mother Teresa Women's University, Kodaikanal, IN
2 SRM University, Ramapuram, IN
1 Mother Teresa Women's University, Kodaikanal, IN
2 SRM University, Ramapuram, IN
Source
Current Science, Vol 110, No 4 (2016), Pagination: 687-691Abstract
Liver cancer leads to more number of human deaths nowadays. Patient survival chances can be increased by early detection of the tumour. Texture analysis based on moment features for CT liver scan images is proposed here. The texture feature is extracted by local binary pattern and statistical features are extracted by Legendre moments. This communication presents a comparative analysis between these Legendre moments, local binary pattern and combined features. The classification accuracy of 96.17% is obtained for CT liver images. The experimental result shows that better texture classification is obtained using the proposed method.Keywords
CT Liver Images, Feature Extraction, Legendre Moments, Local Binary Pattern.Full Text
References
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