By a News Reporter-Staff News Editor at Life Science Weekly -- Research findings on Life Science Research are discussed in a new report. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Image registration is widely used in many fields, but the adaptability of the existing methods is limited. This work proposes a novel image registration method with high precision for various complex applications.”
Financial supporters for this research include Natural Science Foundation of Beijing Municipality, National Natural Science Foundation of China, The National High Technology Research and Development Program of China.
Our news editors obtained a quote from the research from the Beijing Institute of Technology, “In this framework, the registration problem is divided into two stages. First, we detect and describe scale-invariant feature points using modified computer vision-oriented fast and rotated brief (ORB) algorithm, and a simple method to increase the performance of feature points matching is proposed. Second, we develop a new local constraint of rough selection according to the feature distances. Evidence shows that the existing matching techniques based on image features are insufficient for the images with sparse image details. Then, we propose a novel matching algorithm via geometric constraints, and establish local feature descriptions based on geometric invariances for the selected feature points. Subsequently, a new price function is constructed to evaluate the similarities between points and obtain exact matching pairs. Finally, we employ the progressive sample consensus method to remove wrong matches and calculate the space transform parameters.”
According to the news editors, the research concluded: “Experimental results on various complex image datasets verify that the proposed method is more robust and significantly reduces the rate of false matches while retaining more high-quality feature points.”
For more information on this research see: A novel image registration approach via combining local features and geometric invariants. Plos One , 2018;13(1):e0190383. (Public Library of Science - www.plos.org; Plos One - www.plosone.org)
The news editors report that additional information may be obtained by contacting Y. Lu, Key Lab of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing Institute of Technology, Beijing, People’s Republic of China. Additional authors for this research include K. Gao, T. Zhang and T. Xu.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1371/journal.pone.0190383. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-01-16), Study Data from Beijing Institute of Technology Update Understanding of Life Science Research (A novel image registration approach via combining local features and geometric invariants), Life Science Weekly, 3200, ISSN: 1552-2474, BUTTER® ID: 014985348
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