İrfan EMRE, Türker TUNCER, Sengul DOGAN, Murat KÜRŞAT, Osman GEDİK, Yaşar KIRAN

An Accurate HOG based Exemplar Pyramid Method for Image Classification of Astragalus L. Taxa

As known from the literature, machine learning (ML) is one of the popular researches have been used variable areas. In this work, a novel exemplar pyramid method is presented to accurately classify Astragalus L. taxa by using their chromosome images. To implement ML to biological images, the proposed exemplar pyramid method is used. Histogram of Oriented Gradients (HOG) is utilized as feature generator. The proposed exemplar pyramid method consists of preprocessing, feature generation and concatenation, feature selection and classification phase. 10 classifiers are chosen to train and test the extracted features. According to results, the proposed exemplar pyramid generates discriminative features. because five of the used 10 classifiers achieved 100.0% classification rate.

Keywords:

Chromosome, Astragalus, Image processing, HOG, Plant classficaiton,

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