Open AccessApplication of Digital Image Segmentation of Plantation Fruit Classification in Samarinda Agricultural Polytechnic
Author(s) -
Ella Pajriyani,
Eny Maria,
Rusmini Rusmini
Publication year - 2020
Publication title -
tepian
Language(s) - English
Resource type - Journals
eISSN - 2721-5369
pISSN - 2721-5350
DOI - 10.51967/tepian.v1i1.47
Subject(s) - thresholding , artificial intelligence , image segmentation , digital image processing , digital image , computer science , process (computing) , image processing , segmentation , artificial neural network , computer vision , image (mathematics) , contextual image classification , pattern recognition (psychology) , operating system
Applications of Digital Image Segmentation of Plantation Fruit Classification in Samarinda State Agricultural Polytechnic Based on Form The development of computer technology at this time has brought significant progress in various aspects of human life. Such development is supported by the availability of increasingly high hardware and software, one of the technologies experiencing rapid development is image processing. Image processing is a system where the process is carried out by entering an image and the result is also an image. Currently the use of digital images is widely used in various fields one of which is in the plantation sector. Therefore, the purpose of this study is to create a digital image segmentation application for the classification of plantation fruit based on shape. The method used for image segmentation is the Thresholding method, while the image classification uses the Artificial Neural Network (ANN) method. The accuracy generated by the system both in the training process and testing shows that the method used can classify fruit images well