Serrurier Marseille E-books > Nonfiction 13 > Download e-book for iPad: Image Feature Detectors and Descriptors : Foundations and by Ali Ismail Awad, Mahmoud Hassaballah

Download e-book for iPad: Image Feature Detectors and Descriptors : Foundations and by Ali Ismail Awad, Mahmoud Hassaballah

By Ali Ismail Awad, Mahmoud Hassaballah

ISBN-10: 3319288520

ISBN-13: 9783319288529

ISBN-10: 3319288547

ISBN-13: 9783319288543

This ebook presents readers with a variety of top of the range chapters that hide either theoretical recommendations and useful purposes of photograph characteristic detectors and descriptors. It serves as reference for researchers and practitioners through that includes survey chapters and learn contributions on picture characteristic detectors and descriptors. also, it emphasizes numerous key phrases in either theoretical and functional elements of photo function extraction. The key words contain acceleration of characteristic detection and extraction, implantations, picture segmentation, evolutionary set of rules, ordinal measures, in addition to visible speech recognition.

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Additional resources for Image Feature Detectors and Descriptors : Foundations and Applications

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But, if the image is an aerial view of a city, the corner detector is suitable to find man-made structures. Furthermore, selecting a detector and a descriptor that addresses the image degradation is very important. For example, if there is no scale change present, a corner detector that does not handle scale is highly desirable; while, if image contains a higher level of distortion, such as scale and rotation, the more computationally intensive SURF Image Features Detection, Description and Matching 39 feature detector and descriptor is a adequate choice in that case.

27(8), 1265–1278 (2005) Image Features Detection, Description and Matching 43 16. : Texture classification from random features. IEEE Trans. Pattern Anal. Mach. Intell. 34(3), 574–586 (2012) 17. : SURF features for efficient robot localization with omnidirectional images. In: International Conference on Robotics and Automation, pp. 3901–3907. Rome, Italy, 10–14 Apr, 2007 18. : SIFT, SURF & seasons: appearance-based long-term localization in outdoor environments. Rob. Auton. Syst. 58(2), 149–156 (2010) 19.

9(5), 741–750 (2015) 83. : Image matching using generalized scale-space interest points. J. Math. Imaging Vis. 52(1), 3–36 (2015) 84. The oxford data set is available at (last visit, Oct. html A Review of Image Interest Point Detectors: From Algorithms to FPGA Hardware Implementations Cesar Torres-Huitzil Abstract Fast and accurate image feature detectors are an important challenge in computer vision as they are the basis for high-level image processing analysis and understanding. However, image feature detectors cannot be easily applied in real-time embedded computing scenarios, such as autonomous robots and vehicles, mainly due to the fact that they are time consuming and require considerable computational resources.

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Image Feature Detectors and Descriptors : Foundations and Applications by Ali Ismail Awad, Mahmoud Hassaballah


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