Paper Contents
Abstract
Text recognition is critical in various domains, including driving assistance, handwriting recognition. Scene text detection using Deep Learning has more demand for recognising and locating text in natural images. Unlike traditional Optical Character Recognition (OCR) systems have been designed for structured environments, whereas scene text detection deals with unstructured and unorganised text such as street signs, product labels and handwritten notes. Deep Learning methods are used to detect the patterns, shapes, fonts. This study includes Fusion Neural Networks (FNN) which uses Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) which can automatically learns to detect a text or segments from complex backgrounds. The system integrates CNN for feature extraction and RNN for feature classification and prediction.Usage of Bi-directional Grated Recurrent Unit (Bi-GRU) for forward and backward pass in Deep Learning models results in improved accuracy. The integration of Deep Learning models for Scene Text Detection are more accurate than traditional systems in real world scenarios.
Copyright
Copyright © 2024 KONALA SUHAN JAYAKAR. This is an open access article distributed under the Creative Commons Attribution License.
