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Analysis of Different Feature Description Algorithm in object Recognition

Sirshendu Hore, Sankhadeep Chatterjee, Shouvik Chakraborty, Rahul Kumar Shaw

Source Title: Feature Detectors and Motion Detection in Video Processing

ISBN13: 9781522510253|ISBN10: 1522510257|EISBN13: 9781522510260

DOI: 10.4018/978-1-5225-1025-3.ch004

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MLA

Hore, Sirshendu, et al. "Analysis of Different Feature Description Algorithm in object Recognition." Feature Detectors and Motion Detection in Video Processing, edited by Nilanjan Dey, et al., IGI Global, 2017, pp. 66-99. https://doi.org/10.4018/978-1-5225-1025-3.ch004

APA

Hore, S., Chatterjee, S., Chakraborty, S., & Shaw, R. K. (2017). Analysis of Different Feature Description Algorithm in object Recognition. In N. Dey, A. Ashour, & P. Patra (Eds.), Feature Detectors and Motion Detection in Video Processing (pp. 66-99). IGI Global. https://doi.org/10.4018/978-1-5225-1025-3.ch004

Chicago

Hore, Sirshendu, et al. "Analysis of Different Feature Description Algorithm in object Recognition." In Feature Detectors and Motion Detection in Video Processing, edited by Nilanjan Dey, Amira Ashour, and Prasenjit Kr. Patra, 66-99. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1025-3.ch004

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Abstract

Object recognition can be done based on local feature description algorithm or through global feature description algorithm. Both types of these descriptors have the efficiency in recognizing an object quickly and accurately. The proposed work judges their performance in different circumstances such as rotational effect scaling effect, illumination effect and blurring effect. Authors also investigate the speed of each algorithm in different situations. The experimental result shows that each one has some advantages as well as some drawbacks. SIFT (Scale Invariant Feature Transformation) and SURF (Speeded Up Robust Features) performs relatively better under scale and rotation change. MSER (Maximally stable extremal regions) performs better under scale change, MinEigen in affine change and illumination change while FAST (Feature from Accelerated segment test) and SURF consume less time.

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Analysis of Different Feature Description Algorithm in object Recognition

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