Optimally configured convolutional neural network for Tamil Handwritten Character Recognition by improved lion optimizat
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Optimally configured convolutional neural network for Tamil Handwritten Character Recognition by improved lion optimization model R. Babitha Lincy 1 & R. Gayathri 2 Received: 19 February 2020 / Revised: 17 August 2020 / Accepted: 28 August 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
In recent data, Optical character recognition (OCR) systems have laid hands in the field of most popular language recognitions. Unlike other languages, the Tamil language is more complex to recognize, and hence considerable efforts have been laid in literature. However, the models are not yet well-organized for precise recognition of Tamil characters. Thus, the current research work develops a novel Tamil Handwritten Character Recognition approach by following two major processes, viz. pre-processing and recognition. The pre-processing phase encloses RGB to grayscale conversion, binarization with thresholding, image complementation, morphological operations, and linearization. Subsequently, the pre-processed image after linearization is subjected to recognition via an optimally configured Convolutional Neural Network (CNN). More particularly, the fully connected layer and weights are fine-tuned by a new Self Adaptive Lion Algorithm (SALA) that is the conceptual improvement of the standard Lion Algorithm (LA). The performance of the proposed work is compared and proved over other state-of-the-art models with respect to certain performance measures. Keywords Tamil character recognition . Pre-processing . Otsu’s Thresholding . Convolutional neural network . Optimization Abbreviations OCR Optical Character Recognition
* R. Babitha Lincy [email protected] R. Gayathri [email protected]
1
ECE/ Information and Communication Engineering, Sri Venkateswara College of Engineering, Anna University, Sriperumbudur, India
2
ECE, Sri Venkateswara College of Engineering, Sriperumbudur Pennalur, Tamilnadu 602117, India
Multimedia Tools and Applications
TCR CNN LA SALA HTCR MK ANN EHO EHO-NN RNN SVM FPR FNR FOR FDR BM MCC NPV HCCR PCA KNN NFC-Ntt SOM SBIR FC
Tamil Character Recognition Convolutional Neural Network Lion Algorithm Self Adaptive Lion Algorithm Handwritten Tamil Character Recognition Markedness Artificial Neural Network Elephant Herding Optimization Elephant Herding Optimization With Neural Network Recurrent Neural Network Support Vector Machine False Positive Rate False Negative Rate False Omission Rate False Discovery Rate Bookmaker Informedness Matthews Correlation Coefficient Negative Predictive Value Handwritten Chinese Characters Recognition Principal Component Analysis Kohonen neural network Non-Fully-Connected Network Self Organizing Map Sketch-Based Image Retrieval Fully Connected
1 Introduction Over the decades, the handwriting continues to persist as a tool in information communication and recordings of the day-to-day life even after the introduction of advanced technologies in the faster revolving technological growth. The character recognition is crucial as notepad comes along
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