Comparative Study of Exact Continuous Orthogonal Moments Applications : Local Feature Extraction and Data Compression

Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2017, Vol 5, Issue 4

Abstract

This paper present an improved reconstruction algorithm of the multigray level images based on overlapping block method using exact continuous moments computation: Legendre , Zernike, PseudoZernike and Gegenbauer moments . We solve the artifact issue caused by unitary block reconstruction which affects the visual image quality. This method aim to ensure high accuracy and low computation time, using only small finite number of moments. Our approaches aims to introduce these moments in the field of data compression and local feature extraction for pattern recognition. Experimental results show the superiority of our proposed approaches over the existing methods.

Authors and Affiliations

Zaineb Bahaoui, Rachid Benouini, Hakim EL Fadili, Khalid Zenkouar, Arsalane Zarghili

Keywords

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  • EP ID EP310027
  • DOI 10.14738/tmlai.54.3226
  • Views 99
  • Downloads 0

How To Cite

Zaineb Bahaoui, Rachid Benouini, Hakim EL Fadili, Khalid Zenkouar, Arsalane Zarghili (2017). Comparative Study of Exact Continuous Orthogonal Moments Applications : Local Feature Extraction and Data Compression. Transactions on Machine Learning and Artificial Intelligence, 5(4), 524-539. https://europub.co.uk/articles/-A-310027