Found 2 Documents
Journal : Scientific Journal of Informatics

Scientific Journal of Informatics Vol 6, No 2 (2019): November 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i2.20143


Traffic accident is one of the causes of death in the world. One of them is traffic accidents on motorcyclist not wearing helmets. To overcome this problem, several researchers have developed detection system of motorcyclist not wear helmet. This system consists of motorcycle detection and motorcyclist head detection. On motorcycle detection, accuracy still needs to be improved. For this reason, this paper proposed motorcycle detection by adding image improvement processes that are enhancing contrast and adding object positioning features.The techniques proposed in this study are divided into 3 stages of image enhancement, feature extraction, and classification. The image enhancement stage consists of enhance contrast, convert RGB image to gray scale, background subtraction, convert gray scale image to binary, closing operation, and small object removal. The features used in this paper are the features of the object area, the circumference of the object, and the location of the object, while the method for classification process using back-propagation neural network and SVM. The proposed method resulted in an accuracy of 96.97%. Error occurs in all image test data not motorcycle objects detected as motorcycle objects. This error is caused because the pixel value between the objects in the image with the background color has a level of difference is too small, so it is detected as an object not a motorcycle.
Color Space to Detect Skin Image: The Procedure and Implication Endah, Sukmawati Nur; Kusumaningrum, Retno; Wibawa, Helmie Arif
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.12013


Skin detection is one of the processes to detect the presence of pornographic elements in an image. The most suitable feature for skin detection is the color feature. To be able to represent the skin color properly, it is needed to be processed in the appropriate color space. This study examines some color spaces to determine the most appropriate color space in detecting skin color. The color spaces in this case are RGB, HSV, HSL, YIQ, YUV, YCbCr, YPbPr, YDbDr, CIE XYZ, CIE L*a*b*, CIE L*u* v*, and CIE L*ch. Based on the test results using 400 image data consisting of 200 skin images and 200 non-skin images, it is obtained that the most appropriate color space to detect the color is CIE L*u*v*.