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Archana, D.
- Palatal Rugae and Dental Work Information-Tools of Human Identification
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Authors
Affiliations
1 Sri Sairam Engineering College, Chennai-44, IN
1 Sri Sairam Engineering College, Chennai-44, IN
Source
Biometrics and Bioinformatics, Vol 4, No 7 (2012), Pagination: 318-323Abstract
Dental biometrics is used in forensic dentistry to identify or verify persons. This paper presents a method for human identification based on dental work information along with palatal rugae recognition which is considered to be unique for each person just like the finger prints. The proposed method works with three main processing steps: segmentation (feature extraction), creation of a dental code, and matching. In the segmentation step, seed points of the dental works are detected by thresholding. The final segmentation is obtained with a snake (active contour) algorithm. The dental code is defined from the position (upper or lower), the size of the dental works, and distance between neighboring dental works. The matching stage is performed with the Edit distance (Levenshtein distance). The palatal rugae is also considered. By superimposing the rugae patterns of unknown with those in database the identification is made easier.
- A Node Location Algorithm Based on Improved Grasshopper Optimization in Wireless Sensor Network
Abstract Views :92 |
PDF Views:1
Authors
D. Archana
1,
S. Prakasam
1
Affiliations
1 Department of Computer Science and Application, Sri Chandrasekharendra Saraswathi Viswa Maha Vidyalaya University, IN
1 Department of Computer Science and Application, Sri Chandrasekharendra Saraswathi Viswa Maha Vidyalaya University, IN
Source
ICTACT Journal on Communication Technology, Vol 13, No 3 (2022), Pagination: 2767-2773Abstract
As the use of swarm intelligence algorithms grows, so does the interest in placing nodes in a Wireless Sensor network. For this reason, the RSSI range model positioning algorithm has been replaced by a more accurate one. With the help of this paper, you can solve complex structural optimization problems with the Grasshopper Optimization Algorithm (GOA). Optimization problems can be solved using this algorithm, which was inspired by the behaviour of grasshopper colonies. CEC2005 is used to test the GOA algorithm quality and quantitative performance. Trusses with a total of 53 and 3 cantilever beams are used to demonstrate the design practicality. It appears that the proposed algorithm outperforms well-known and recently developed algorithms in this area. GOA ability to solve real-world problems with unknown search spaces is demonstrated by its use in the real world.Keywords
WSN (Wireless Sensor Network), GOA (Grasshopper Optimization Algorithm), RSSI, Whale Optimization AlgorithmReferences
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