PDA-based text localization system using client/server architecture

초록

Recently, several research results of image processing are proposed on the mobile vision systems. Many CPUs for Personal Digital Assistant(PDA) are integer CPUs, which have no floating-computation component. It results in slow computation of the algorithms constructed by using neural networks, which have much floating-computation. In this paper, in order to resolve this weakness, we propose an effective text localization system with the Client(PDA)/Server(PC) architecture which is connected to each other with a wireless LAN. The Client(PDA) compresses tentative text localization results in JPEG format for minimizing the transmission time to the Server(PC). The Server(PC) uses both the Multi-Layer Perceptron(MLP)-based texture classifier and Connected Components(CCs)-based filtering for a precise text localization based on the Client(PDA)'s tentative extracting results. The proposed method leads to not only faster running time but also efficient text localization.