An MRF Model-Based Approach to Simultaneous Recovery of Depth and Restoration from Defocused Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Depth from defocus estimation in spatial domain
Computer Vision and Image Understanding
A dynamic quasi-newton method for model independent visual servoing
A dynamic quasi-newton method for model independent visual servoing
On defocus, diffusion and depth estimation
Pattern Recognition Letters
Task-independent robotic uncalibrated hand-eye coordination based on the extended state observer
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image enhancement using the modified ICM method
IEEE Transactions on Image Processing
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In order to perform an effective and reliable automatic microassembly, depth information estimation is the first task, a blur parameter model of defocus image based on Markov random field has been present. It converts problem of depth estimation into optimization problem. An improved Iterated Conditional Modes Algorithm has been applied to complete optimization problem, which the select of initial point employed Least squares estimate algorithm prevents that the result gets into local optimization. The visual servoing is the second task. For avoiding the complicated calibration of intrinsic parameter of camera, We apply an improved broyden's method to estimate the image jacobian matrix online, which employs chebyshev polynomial to construct a cost function to approximate the optimization value, obtaining a fast convergence for online estimation. Last, we design a PD controller to control micro-robot for completing the visual servo task. The experiments of micro-assembly of micro parts in microscopes confirm that the proposed methods are effective and feasible.