Automatic word detection system for document image using mobile devices

Abstract

In the current age of ubiquitous computing age that uses high bandwidth network, wearable and hand-held mobile devices with small cameras and wireless communication will be widespread in the near future. Thus, computer vision and image processing for mobile devices have recently attracted a lot of attention. Especially, many approaches to detect image texts containing useful information for automatic annotation, indexing, and structuring of image are important for a prerequisite stage of recognition in dictionary application using mobile devices equipped with a camera. To detect image texts on the mobile devices that have limited computational resources, recent works are based on two methodologies; the image texts are detected not by automatically but by manually using stylus pen to reduce the computational resources, and the server is used to detect image texts requiring many floating-computations. The main disadvantage of the manual method is that users directly select tentative text regions, and recall and precision rates are determined by the selected regions. The second method to automatically detect the image texts is difficult to perform it in real-time, due to transmission time between the mobile device and the server. Accordingly, this paper proposes a real-time automatic word detection system without support of the server. To minimize the computational time, one word in the central region of the image is considered as a target of the system. The word region is tentatively extracted by using edge density and window transition, and the tentatively extracted region is then verified by measuring uniform distribution among sub-windows of the extracted region. In the experiments, the proposed method showed high precision rates for one word in the central region of the image, and showed fast computational time on the mobile devices. © Springer-Verlag Berlin Heidelberg 2007.