Erez, M. EmreKaya, YilmazÇaliskan, Abidin2024-12-242024-12-242013978-146735562-9https://doi.org10.1109/SIU.2013.6531332https://hdl.handle.net/20.500.12604/37322013 21st Signal Processing and Communications Applications Conference, SIU 2013 -- 24 April 2013 through 26 April 2013 -- Haspolat -- 98109In this study, a computer vision system has been developed to separate the pollen grains of plants according to their taxonomic categories without the help of an expert person. Pollen grains have a complex threedimensional structure however they can be distinguished from one to another with their specific features. In the research, for the classification of pollen images the local edge patterns (LEP) were used. The proposed system is consists of three stages. At first Stage, Sobel edge detection algorithm was applied to pollen images to obtained new images that have prominent structural features. At the second stage LEP features were obtained and at the last stage the classification process was performed by machine learning methods by LEP features. The 98.48% classification success were obtained by LEP features. © 2013 IEEE.trinfo:eu-repo/semantics/closedAccessLocal binary patternPollenPollen identificationStructural featuresConference ObjectN/A2-s2.0-8488091308010.1109/SIU.2013.6531332