Paper Info
Title
Color Decision System Based on Deep Learning and Fuzzy Inference System.
Abstract
Autonomous driving system has become a hot issue. Similar to autonomous driving system, Autonomous Guided Vehicle (AGV) works in industry field. It is controlled by its autonomous driving system. This system detects the driving environment by using sensors such as vision sensor, laser sensor, ultrasonic sensor and so on. Among these sensors, vision sensor can obtain various kinds of the information of the environment. In an image, which is captured by vision sensor, the environment is represented by its color, shape and so on. Vision-AGV where vision sensor is mounted can be controlled by the colorful sign like the traffic light. To recognize the sign for controlling the AGV, it is necessary to detect the sign and analyze the meaning of the this sign. Faster Regions with Convolutional Neural Network features (Faster R-CNN) is applied to detect the sign. To analyze the meaning of the color sign, RGB color space, which is well known and consists of primary colors, can be used. However, it is difficult to analyze the color sign by using only RGB color space. Therefore, the proposed method is designed for detecting and recognizing the color of the sign with CIE L*a*b* color space. To improve the effect of the analysis, RGB and CIE L*a*b* color space are combined. Based on RGB, CIE L*a*b* and Peak Signal-toNoise Ratio (PSNR), the color of the region which is extracted by Faster R-CNN is determined by the fuzzy inference system. As experimental results, the proposed method can detect the sign and analyze the color of this sign.
Year
DOI
Venue
2018
10.1109/SCIS-ISIS.2018.00049
Joint International Conference on Soft Computing and Intelligent Systems SCIS and International Symposium on Advanced Intelligent Systems ISIS
Keywords
Field
DocType
Color Decision System,Deep Learning,Fuzzy Inference System,Image Processing,Peak Signal-to-noise Ratio
Computer science,Decision system,Artificial intelligence,Deep learning,Machine learning,Fuzzy inference system
Conference
ISSN
Citations 
PageRank 
2377-6870
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Eun-Kyeong Kim162.59
JongEun Park2124.21
Jin Yong Kim300.34
Sungshin Kim421064.17