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Dongxiang Zhou
Researcher at National University of Defense Technology
Publications - 31
Citations - 372
Dongxiang Zhou is an academic researcher from National University of Defense Technology. The author has contributed to research in topics: Image segmentation & Feature extraction. The author has an hindex of 7, co-authored 31 publications receiving 329 citations.
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Proceedings ArticleDOI
An algorithm for extrinsic parameters calibration of a camera and a laser range finder using line features
TL;DR: This paper proposes to design a right-angled triangular checkerboard and to employ the invisible intersection points of the laser range finder's slice plane with the edges of theCheckerboard to set up the constraints equations.
Journal ArticleDOI
Accurate Segmentation of Partially Overlapping Cervical Cells Based on Dynamic Sparse Contour Searching and GVF Snake Model
TL;DR: This paper considers the cell contour extraction as a contour points locating problem and proposes an effective and robust framework for segmentation of partially overlapping cells in cervical smear images.
Proceedings ArticleDOI
Automatic identification of mycobacterium tuberculosis from ZN-stained sputum smear: Algorithm and system design
TL;DR: An automated system for TB identification, which consists of an automatic microscope, an image-based autofocus algorithm and an images-based TB identification algorithm, which can automatically capture a large number of clear images on sputum sample and process all the images in real time to identify the bacilli and count their number.
Proceedings ArticleDOI
3D reconstruction based on SIFT and Harris feature points
TL;DR: A new 3D reconstruction method using feature points extracted by the SIFT and Harris corner detector to obtain more vivid and detailed 3D information is presented.
Proceedings ArticleDOI
An efficient and robust corner detection algorithm
TL;DR: This paper proposes an improved SUSAN corner detector that adopts an adaptive multi-threshold strategy based on local brightness rather than one threshold for the whole image, and divides the circular mask area of SUSan into two or more parts.