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Superpixel over-segment image into meaningful clusters so that pixels in each cluster belong to one object. Many state-of-art superpixel algorithms have to make trade-offs between different concerns. As a result, algorithms that can produce good result in some situations fail in another. In order to take advantage of different algorithms and at the same time avoid their limitation, we propose a new...
The ability to detect and localize an object of interest from a captured image containing a cluttered background is an essential function for an autonomous robot operating in an unconstrained environment. In this paper, we present a novel approach to refining the pose estimate of an object and directly labelling its contours by dense local feature matching. We perform this task using a new image descriptor...
Text detection in complex real images, such as panorama images, remains great challenging in Computer Vision. A general method often focuses on the small test images with single background which makes it easier to do the detection and recognition. In this paper, we find a novel approach, as it can automatically deal with the indoor panorama images which contains distortion and illumination problems...
Identification of error in nonrigid registration is a critical problem in the medical image processing community. We recently proposed an algorithm that we call “Assessing Quality Using Image Registration Circuits” (AQUIRC) to identify nonrigid registration errors and have tested its performance using simulated cases. In this paper, we extend our previous work to assess AQUIRC's ability to detect...
This paper addresses the issue of localising object edge contours in cluttered backgrounds to support robotics tasks such as grasping and manipulation and also to improve the potential perceptual capabilities of robot vision systems. Our approach is based on coarse-to-fine matching of a new recursively constructed hierarchical, dense, edge-localised descriptor, the HexBinary, based on the HexHog descriptor...
Based on Cannypsilas edge detecting criteria, we study two types of the cardinal B-spline wavelets which converge asymptotically to Canny operator and Marr-Hildreth operator respectively, derive the mathematical formulas of the signal-to-noise ratio SNR, the localization L and the nonedge-mean-distance M, and prove that when detecting the object edge, the B-spline wavelet converging to Canny operator...
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