Examination Committee

Prof James SHE, ECE/HKUST (Chairperson)
Prof Wai Ho MOW, ECE/HKUST (Thesis Supervisor)
Prof Jun ZHANG, ECE/HKUST

Abstract

With the prevalence of better sensing capability and computational power in consumer electronic devices, using cameras for communication purpose draws increasing attention from both academia and industry. Extensive works have been done to design efficient printer-camera communication systems, including various famous barcode systems. However, such a print-capture communication channel is complicated due to the sophisticated printing and imaging processes involved. In addition, even with a given model,  the allowable overhead for training the model is severely limited by the high data capacity requirement and the available computational resources in real-world implementation platforms. If a model is accurate but too complicated, it is difficult to be applied in practice and is thus less valuable. On the other hand, if a model is too simplistic, it could be inaccurate and may not give satisfactory performance in practical scenarios.

In this thesis, we propose a new model for the print-and-capture channel, which enables low-overhead training to achieve good accuracy. We first derive a new print-and-capture channel model with an explicit parametric form. Based on the model, an efficient scheme for training the model and equalizing the channel is proposed. To reduce the training overhead, we decompose the channel distortions into three types by utilizing the structure of the proposed parametric form and conduct a sequence of simple estimation steps instead of tackling the whole model all at once. Furthermore, the proposed model is capable of generating the probabilistic information as the demodulation result, allowing the usage of advanced channel codes with soft decision decoding and thus improves the system performance. Finally, a multilevel barcode system based on the proposed channel model is designed for achieving higher data capacity. Experimental results are presented to verify the effectiveness of the proposed model and the superior performance of the multilevel barcode system under realistic scenarios.