TELKOMNIKA Telecommunication, Computing, Electronics and Control
Extraction of object image features with gradation contour

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Extraction of object image features with gradation contour

Contour
Extraction
Feature
Gradation
Image

Image retrieval using features has been used in previous studies including
shape, color, texture, but these features are lagging. With the selection of
high-level features with contours, this research is done with the hypothesis
that images on objects can also be subjected to representations that are
commonly used in natural images. Considering the above matters, we need to
research the feature extraction of object images using gradation contour.
From the results of the gradation contour test results, there is 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.

Fachruddin, Saparudin, Errissya Rasywir, Yovi Pratama, Beni Irawan

http://journal.uad.ac.id/index.php/TELKOMNIKA

May 2, 2021

peri irawan

pdf

english

text