| Summary: | 博士 === 國立交通大學 === 電機與控制工程系所 === 96 === The objective of this thesis is to develop a novel color filter array (CFA) interpolation algorithm for color reproduction of a single image sensor and a robust visual tracking control system for vision-based motion control of a wheeled mobile robot. Most digital cameras employ a single image sensor covered with a Bayer CFA to capture a Bayer mosaic image. A full-color image is then reconstructed from the captured Bayer mosaic image through a color reproduction process, commonly known as CFA interpolation or CFA demosaicing. To reconstruct the full-color images with high fidelity, a novel heterogeneity-projection hard-decision (HPHD) algorithm combined with a new color-difference based edge-adaptive (CDEA) CFA interpolation method is proposed for color reproduction of Bayer mosaic images. The proposed HPHD algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which the direction of interpolation is decided before performing the interpolation. On the other hand, the proposed CDEA CFA interpolation method devotes to reproduce color values with fewer color artifacts by adding the high-frequency information of green channel to other color channels. Compared with three recently reported CFA interpolation techniques, the proposed HPHD-CDEA method outperforms all of them in both quantitative and visual comparisons by utilizing twenty-five natural images from Kodak PhotoCD.
In the design of visual tracking control, a robust visual tracking control system, which consists of a visual tracking controller (VTC) and a visual state estimator (VSE), is proposed for a wheeled mobile robot equipped with a tilt camera. A novel dual-Jacobian visual interaction model is first derived to help the design of VTC and VSE. The VSE aims to estimate the optimal system state and target motion in the image plane directly, and the VTC then calculates the robot’s control velocities by using the estimation results from VSE. To handle the uncertainties encountered in practical visual tracking control system, the VSE can overcome the disturbances caused by both image noise and temporary occlusion uncertainties. On the other hand, the VTC not only possesses some degree of robustness against the system model uncertainties, but also overcomes the unmodelled quantization effect in the velocity commands. Therefore, by combining the proposed VTC with the proposed VSE, the visual tracking control system is robust to the uncertainties of image noise, system model, velocity quantization and temporary occlusion. Computer simulations and experimental results validate the effectiveness of the proposed visual tracking control system, in terms of tracking performance, system convergence, and robustness.
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