We present a homography-based approach to detect the ground plane from monocular sequences captured by a robot platform. By assuming that the camera is fixed on the robot platform and can at most rotate horizontally, we derive the constraints that the homograph of the ground plane must satisfy and then use these constraints to design algorithms for detecting the ground plane. Due to the reduced degree of freedom, the resultant algorithm is not only more efficient and robust, but also able to avoid false detection due to virtual planes. We present experiments with real data from a robot platform to validate the proposed approaches.

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The capability of using Focused Ion Beam (FIB) for milling microchannels is experimentally and theoretically investigated. Microchannel structures are fabricated by a NanoFab 150 FIB machine, using an Arsenic (As2+) ion source. A beam current of 5 pA at 90 keV accelerating energy is used. Several microchannel patternings are milled at various dwell times at pixel spacing of 14.5 nm on top of a 60 nm gold-coated silicon wafer. An analytical/numerical model is developed to predict the FIB milling behavior. By comparing with the experimental measurements, the model predictions have been demonstrated to be reliable for guiding and controlling the milling processes.

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In this paper, we present an algorithm for automatically generating pencil-sketch like drawings from personal photos. On top of the core step of gradient computation, some proper transformations are introduced to achieve the best visual effects. It is found that the popular Sobel operator and Laplacian operator are both not desirable for this task, and thus we propose a computationally simple algorithm for gradient estimation. Experimental results show that the proposed method can generate visually appealing pencil-sketch like images from personal photos.