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An Intelligent Heuristic Manta-Ray Foraging Optimization and Adaptive Extreme Learning Machine for Hand Gesture Image Recognition

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Big Data Mining and Analytics 2023年第3期6卷 321-335页

作者： Seetharam Khetavath Navalpur Chinnappan Sendhilkumar Pandurangan Mukunthan selvaganesan jana Lakshmanan Malliga Subburayalu Gopalakrishnan Sankuru Ravi Chand Yousef Farhaoui Department of Electronics and Communication Engineering Chaitanya(Deemed to be University)Warangal 506001India. Department of Electronics and Communication Engineering Sri Indu College of Engineering&TechnologySherigudaHyderabad 501510India. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600062India. Department of Electronics and Communication Engineering Malla Reddy Engineering College for Women(Autonomous)Telangana 500100India. Department of Electronics and Communication Engineering Nalla Narasimha Reddy Education Society’s Group of Institutions-Integrated CampusHyderabad 500088India. STI Laboratory the IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsErrachidia 52000Morocco.

The development of hand gesture recognition systems has gained more attention in recent days,due to its support of modern human-computer ***,sign language recognition is mainly developed for enabling communication between deaf and dumb *** conventional works,various image processing techniques like segmentation,optimization,and classification are deployed for hand gesture ***,it limits the major problems of inefficient handling of large dimensional datasets and requires more time consumption,increased false positives,error rate,and misclassification ***,this research work intends to develop an efficient hand gesture image recognition system by using advanced image processing *** image segmentation,skin color detection and morphological operations are performed for accurately segmenting the hand gesture ***,the Heuristic Manta-ray Foraging Optimization(HMFO)technique is employed for optimally selecting the features by computing the best fitness ***,the reduced dimensionality of features helps to increase the accuracy of classification with a reduced error ***,an Adaptive Extreme Learning Machine(AELM)based classification technique is employed for predicting the recognition *** results validation,various evaluation measures have been used to compare the proposed model’s performance with other classification approaches.

关键词： hand gesture recognition skin color detection morphological operations Multifaceted Feature Extraction(MFE)model Heuristic Manta-ray Foraging Optimization(HMFO) Adaptive Extreme Learning Machine(AELM)

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