BOVW FOR CLASSIFICATION IN GEOMETRICS SHAPES

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ABSTRACT

The classification of forms is a process used in various areas, to perform a classification based on the manipulation of shape contours it is necessary to extract certain common characteristics, it is proposed to use the bag of visual words model, this method consists of three phases: detection and extraction of characteristics, representation of the image and finally the classification. In the first phase of detection and extraction the SIFT and SURF methods will be used, later in the second phase a dictionary of words will be created through a process of clustering using K-means, EM, K-means in combination with EM, finally in the Classification will be compared algorithms of SVM, Bayes, KNN, RF, DT, AdaBoost, NN, to determine the performance and accuracy of the proposed method..

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Zurita, B., Luna, L., Hernández, J., & Ramírez, F. (2018). BOVW for classification in geometrics shapes. Applied Computer Science, 14(4), 5-11. doi:10.23743/acs-2018-25
Zurita, Baldemar, Luís Luna, José Hernández, and Federico Ramírez. "Bovw for Classification in Geometrics Shapes." Applied Computer Science 14, no. 4 (2018): 5-11.
B. Zurita, L. Luna, J. Hernández, and F. Ramírez, "BOVW for classification in geometrics shapes," Applied Computer Science, vol. 14, no. 4, pp. 5-11, 2018.
Zurita B, Luna L, Hernández J, Ramírez F. BOVW for classification in geometrics shapes. Applied Computer Science. 2018;14(4):5-11.