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• W2755121805 abstract "Feature detection and matching is an important step in many object detection and tracking algorithms. This paper discusses methods to improve upon our previous work on the SYnthetic BAsis feature descriptor (SYBA) algorithm, which describes and compares image features in an efficient and discrete manner. SYBA utilizes synthetic basis images overlaid on a feature region of interest (FRI) to generate binary numbers that uniquely describe the feature contained within the image region. These binary numbers are then used to compare against feature values in subsequent images for matching. However, in a non-ideal environment the accuracy of the feature matching suffers due to variations in image scale, and rotation. This paper introduces a new version of SYBA which processes FRI's such that the descriptions generated with SYBA for feature matching are rotation and scale invariant." @default.
• W2755121805 created "2017-09-25" @default.
• W2755121805 creator A5020867725 @default.
• W2755121805 creator A5065513075 @default.
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• W2755121805 date "2017-09-01" @default.
• W2755121805 modified "2023-09-26" @default.
• W2755121805 title "Robust synthetic basis feature descriptor" @default.
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• W2755121805 doi "https://doi.org/10.1109/icip.2017.8296540" @default.
• W2755121805 hasPublicationYear "2017" @default.
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