Identification of jasmine flower (Jasminum sp.) based on the shape of the flower using sobel edge and k-nearest neighbour

Indonesian Operations Research Association - International Conference on Operations Research 2017

Qur'ania, A.^1 ; Sarinah, I.^1

Computer Science, Faculty of Mathematics and Natural Sciences, Pakuan University, Jalan Pakuan PO BOX 452, Bogor

16143, Indonesia^1

关键词: Accuracy rate;    Closest distance;    Digital image;    Distance values;    K-nearest neighbor method;    K-nearest neighbors;    K-nearest neighbours;    Sobel edge detection;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/332/1/012008/pdf
DOI  :  10.1088/1757-899X/332/1/012008

来源: IOP

【 摘 要 】

People often wrong in knowing the type of jasmine by just looking at the white color of the jasmine, while not all white flowers including jasmine and not all jasmine flowers have white. There is a jasmine that is yellow and there is a jasmine that is white and purple.The aim of this research is to identify Jasmine flower (Jasminum sp.) based on the shape of the flower image-based using Sobel edge detection and k-Nearest Neighbor. Edge detection is used to detect the type of flower from the flower shape. Edge detection aims to improve the appearance of the border of a digital image. While k-Nearest Neighbor method is used to classify the classification of test objects into classes that have neighbouring properties closest to the object of training. The data used in this study are three types of jasmine namely jasmine white (Jasminum sambac), jasmine gambir (Jasminum pubescens), and jasmine japan (Pseuderanthemum reticulatum). Testing of jasmine flower image resized 50 × 50 pixels, 100 × 100 pixels, 150 × 150 pixels yields an accuracy of 84%. Tests on distance values of the k-NN method with spacing 5, 10 and 15 resulted in different accuracy rates for 5 and 10 closest distances yielding the same accuracy rate of 84%, for the 15 shortest distance resulted in a small accuracy of 65.2%.