Text Extraction from Document Images using CNN and LSTM

This research study proposes an advanced system that combines image processing techniques with deep learning models to achieve precise text extraction from images. Our approach in this paper involves several key steps. First, we apply preprocessing techniques to enhance the image quality and clarity of text regions. Next, the proposed method employs image processing algorithms to identify and isolate text regions within the image. To recognize and transcribe the extracted text, the proposed method utilizes deep learning models, specifically convolutional neural networks (CNNs) and recurrent neural networks (RNNs). To train the deep learning model in the proposed method, we generate a labeled dataset by annotating text regions in images. The proposed model highlights the effectiveness of integrating image processing and deep learning techniques in achieving accurate and efficient text extraction from images. The system's performance and flexibility make it a valuable tool for applications that require reliable text extraction capabilities.