Lemp: a Robust Image Feature Descriptor for Retrieval Applications
L Koteswara Rao1, P Rohni2, M Narayana3

1L Koteswara Rao, Professor, Department of ECE, Koneru Lakshmaiah Education Foundation, off Campus, Hyderabad.
2P Rohni, Asst. Professor, Department of CSE, ICFAI Foundation for Higher Education, Hyderabad.
3M Narayana, Professor in ECE, Vardhaman college of Engineering, Hyderabad, India.
Manuscript received on September 23, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 4565-4569 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1821109119/2019©BEIESP | DOI: 10.35940/ijeat.A1821.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: line edge magnitude pattern (lemp) is proposed in this paper. Line edge distribution is used to denote local region of an image. Popular texture descriptors such as lbp deal with a comparison of centre pixel with neighbors and thus encode the information. In lemp ,pixel at the centre is replaced by edge values of neighbors. Discriminating information provided by line edges makes this method different from many of the existing methods. Magnitude is also added to the line edge information in order to make the feature descriptor more effective and robust. Performance of lemp method is estimated with corel database. Standard metrics such as recall, precision and average retrieval rate are determined for comparison purpose. Experimental values exhibit a notable improvement in the performance.
Keywords: Retrieval , Patterns, Magnitude, Edge.