The existing embedded Chinese input systems are restricted by problems such as single type of input device, low inefficiency and poor user experience. To solve these problems, this paper put forward a MicroWindows-based intelligent Chinese input system. First messages from different types of device were packed and delivered in the device input layer. Then the delivered messages were centrally treated by uniformly encoding and distributing in the message processing center. Finally the improved N-gram model and user model were combined to implement Chinese input method. The experiments in Microprocessor without Interlocked Piped Stages (MIPS) and other platform show that this system runs well with fluent and fast Chinese input. The efficiency of input is raised by 35% compared with traditional Chinese input.

To deal with low efficiency and long-time consumption in verifying OSD (On-Screen-Display) of video devices, this paper devised an automatic OSD verification system. The system consisted of three parts. OSD area location was achieved by synthesizing statistical characteristics. Single character was then segmented based on improved Otsu algorithm. Finally, Gabor features and improved BP neural network were used to recognize these characters. The experimental results show that this system costs average 53ms per recognition of one frame with a recognition rate at 92.7%.