A Combined Approach for Text Detection in Images Using MLP Neural Networks and Image Processing

Text detection in images is an important research area that has attracted the attention of many researchers. Due to the growing image databases, information retrieval from databases in less time and with maximum precision is more important. The low level features which are extracted from the images and videos include metrics of color, texture and shape, although these features can easily be obtained, they do not have enough accuracy to extract the content. Today, text retrieval in images is an important part of content recovery. Detection of vehicle plates, text ads or video frames, book title and addresses in mailing envelopes are among text mining applications. In the current article a method for combing image processing and neural networks for text detection in images is presented. In this approach, after detecting text location in image using MLP (Multiple Layer Perception) neural network structure, the text in the images is detected. Finally, the performance of two neural network MLP and LVQ (Learning Vector Quantization) for text detection are compared. The results show that the MLP neural network with suggested implemented algorithm in this network has a better performance

کلیدواژه ها:

Image Processing ، MLP Neural Networks ، Text Detection ، Wavelet Transform