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Video tracking using scale - invariant feature transform (S.I.F.T.) algorithm
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Scale Invariant Feature Transform using oriented pattern
2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014Image matching plays an important role in many aspects of computer vision. Our proposed method is based on Scale Invariant Feature Transform (SIFT) which is one of the popular image matching methods. The main ideas behind our method are removing the excess keypoints, adding oriented patterns to descriptor, and decreasing the size of the descriptors. By
Mohammad Baghery Daneshvar +2 more
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Keyboard recognition from scale-invariant feature transform
2017 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW), 2017Based on the scale-invariant feature transform, this paper presents an approach to keyboard recognition. Not only the skewed keyboard can be corrected, but also the keys in the keyboard can be located. Experimental results confirm the feasibility of the proposed method.
Ming-Te Chao, Yung-Sheng Chen
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FPGA implementation of scale invariant feature transform
2016 International Conference on Microelectronics, Computing and Communications (MicroCom), 2016Scale Invariant Feature Transform is a competent algorithm for extracting unique features from images. The fact that features extracted are invariant to image scaling, translation, rotation and partially invariant to illumination changes makes it attractive in many computer vision applications involving mobile robots such as obstacle recognition ...
S S Rekha, Y J Pavitra, Prabhakar Mishra
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Scale-Invariant Feature Transform (SIFT)
2016Many real applications require the localization of reference positions in one or more images, for example, for image alignment, removing distortions, object tracking, 3D reconstruction, etc. We have seen that corner points1 can be located quite reliably and independent of orientation.
Wilhelm Burger, Mark J. Burge
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Modified Scale Invariant Feature Transform in omnidirectional images
2009 International Conference on Mechatronics and Automation, 2009The Scale Invariant Feature Transform, SIFT, is invariant to image translation, scaling, rotation, and is partially invariant to illumination changes. But, the time of features extraction and matching is huge, and the number of features is much larger then that is needed.
null Yuquan Wang +3 more
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Visual orientation inhomogeneity based scale-invariant feature transform
Expert Systems with Applications, 2015Provide the evidence of existence of the least important visual orientation.Novel algorithm with high efficiency is proposed to detect and describe local feature.Better performance for detection and matching, comparable performance for recognition. Scale-invariant feature transform (SIFT) is an algorithm to detect and describe local features in images.
Sheng-hua Zhong, Yan Liu, Qing-cai Chen
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Object Recognition by Modified Scale Invariant Feature Transform
2008 Third International Workshop on Semantic Media Adaptation and Personalization, 2008This paper presents a methodology for object recognition. It relies on the extraction of distinctive invariant image features that can be used to find the correspondence between different views of an object or a scene. These features are invariant to image rotation and scaling, they have substantial robustness to changes in viewpoint and illumination ...
null Gul-e-Saman, S. Asif M. Gilani
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Automated Urine Microscopy Using Scale Invariant Feature Transform
Proceedings of the 2019 9th International Conference on Biomedical Engineering and Technology, 2019Urine microscopy is a tedious task that requires utmost care from the technician doing the job. In order to provide clearer images for accurate interpretation of urine samples, microscopic images must be properly focused. Likewise, it is essential for the technician to avoid contamination with the urine sample when doing the task, especially in the ...
Jennifer C. Dela Cruz +5 more
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Thumb Biometric Using Scale Invariant Feature Transform
2017Recently, biometrics technology has been receiving attention as means of personal authentication in smartphone environment. Fingerprint recognition is generally contained in newest smartphones and other biometric methods such as iris recognition are receiving attention.
Naeun Lim +3 more
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