Abstract
Through this paper we present a new algorithm with the help of Scale Invariant Feature Transformation (SIFT) along with fuzzy \( m_{X}^{*} \) oscillation. We propose a fuzzy based similarity measurement technique i.e. fuzzy \( m_{x}^{*} \) oscillation for providing a better precision in face recognition area. First, apply SIFT for finding key points from sketch and digital images and then select the key points for feature extraction. After feature extraction fuzzy \( m_{X}^{*} \) oscillation based classification are used for these values. For experiment we have considered two scenarios which are described in the beginning of Sect. 4. So using this proposed algorithm we will easily able to identify the correct image as an output of face sketch to photo matching. Accuracy of our algorithm describes this work piece concerned on fuzzy \( m_{X}^{*} \) oscillation has achieved its aim of recognizing the face sketches in the SIFT domain.
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Majumder, B., Bhattacharya (Halder), S. (2020). Face Recognition Based on Human Sketches Using Fuzzy Minimal Structure Oscillation in the SIFT Domain. In: Bhattacharjee, A., Borgohain, S., Soni, B., Verma, G., Gao, XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. MIND 2020. Communications in Computer and Information Science, vol 1241. Springer, Singapore. https://doi.org/10.1007/978-981-15-6318-8_27
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DOI: https://doi.org/10.1007/978-981-15-6318-8_27
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