Abstract
Human-centric visual pattern recognition has emerged as one of the most interesting areas of applied research. This is evident from the rising number of publications in this area over the last decade. Perhaps the most prominent area of application is computer vision, where biometric recognition occupies a central part. The need for reliable, accurate, fully automated, and robust biometric recognition systems has motivated intense research in this area. Despite significant progresses being made, the perfect system remains elusive, and research continues on several fronts, the most notable being the construction of highly efficient features for recognition or classification. As Chap. 1 reveals, there are a plethora of features being used for representation of visual patterns.
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Rahman, S.M.M., Howlader, T., Hatzinakos, D. (2019). Conclusion. In: Orthogonal Image Moments for Human-Centric Visual Pattern Recognition. Cognitive Intelligence and Robotics. Springer, Singapore. https://doi.org/10.1007/978-981-32-9945-0_7
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DOI: https://doi.org/10.1007/978-981-32-9945-0_7
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