Extraction of Object Image Features with Gradation Contour

Fachruddin Fachruddin, Saparudin Saparudin, Errissya Rasywir, yovi pratama, Beni Irawan

Abstract


Detection of the number of objects contained in an image can be used, among others, to detect objects in the fetal ultrasound image, the number of vehicles, the number of visitors, the number of passengers, counting the number of audiences, counting the number of oil palm bunches in each cubic truck and many other types of applications. The research was conducted automatically with a research system using the Gradation Contour method. The selection of this method is the implementation of a novelty method that has not been tested other than natural imagery. From the results of the gradation contour test results, there is a linearity between the results of accuracy with the large number of images tested. Therefore it can be said that the influence of the number of images will affect the accuracy of classification. The use of contour gradation can be accepted and treated equally in all image types, so there is no more differentiation between image features. The complexity of the image does not affect the method of extracting features that are only used uniquely by an image. From the results of testing the polynomial coefficient savings data as a result of the gradation contour, the highest result is 81.40% with the highest number of categories and the number of images tested in the category is also higher.

Keywords


Extraction; Feature ;Gradation; Contour ;Image



DOI: http://dx.doi.org/10.12928/telkomnika.v19i6.19491

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