Abstract
Facial detection and recognition is a major problem facing in image processing. Face identity is an important for identifying, searching and authentication purposes. Facial detection is quite common for humans; hence, it is very difficult for the computational device. The human face consists of many complicated multi-dimensions, and it is difficult to identify by a machine. The proposed methodology is used to distinguish human faces in the given multiple images using Viola-Jones algorithm framework and also improving accuracy from the false positive information and true negative information in the given data by using AdaBoost training methods and cascading classification.
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Rani, K.H., Chakkaravarthy, M. (2022). Improving Accuracy in Facial Detection Using Viola-Jones Algorithm AdaBoost Training Method. In: Reddy, V.S., Prasad, V.K., Mallikarjuna Rao, D.N., Satapathy, S.C. (eds) Intelligent Systems and Sustainable Computing. Smart Innovation, Systems and Technologies, vol 289. Springer, Singapore. https://doi.org/10.1007/978-981-19-0011-2_12
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DOI: https://doi.org/10.1007/978-981-19-0011-2_12
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