1. Feature Extraction of the Human Ear Based on Enhanced Active Contour Method.
- Author
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Hemamalini, V., K, Annapurani, Saha, Pinaki, Batra, Kushal, and Chatterjee, Jaydeep
- Subjects
EAR ,HUMAN mechanics ,FEATURE extraction - Abstract
Human ear detection is one of the key features in biometric-based identification and person authentication. Detecting ears for position, dimension, and texture is tedious due to the height and movement of humans. The biometric systems based on ear detection are defaced by the height of humans and specific positions. For this purpose, a multi-feature and multi-contour-based assessment for precise detection is required. To address this problem, this article introduces an Enhanced Active Contour Method (EACM) for improving ear detection precision. The proposed method extracts the textural features for differentiating the antitragus and helix of the human ear. The extracted features are fused using a fuzzy threshold for the maximum possibilities of the ear structures. In verifying the maximum possibilities, the helix and antitragus contours are fused by identifying similar features. The features from the existing dataset are used for verifying the similarity; the similarity succeeding contours are used for detecting human ears. The proposed method maximizes accuracy and precision by 12.99% and 12.79% and reduces extraction time by 11.34%. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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