Paper Info
Title
Automatic brightness adjustment system by fuzzy inference system for object recognition.
Abstract
A camera has been widely used in practical fields with a diversity of purposes recently. There is a variety purpose of photography: images for memory, medical images for diagnosis, images for object recognition, surveillance images, and so on. In case of images for object recognition, the clarity of images is necessary to analyze the images which are obtained using vision sensors. However, a brightness of the image highly depends on the intensity of illumination in the certain environment. Therefore, we propose a method to solve the problems mentioned above by adjusting brightness automatically by utilizing CIE L*a*b* color space and fuzzy inference system. At first, the proposed method adjusts the brightness of a given image by considering both RGB component and L component of CIE L*a*b* color space. Secondly, the proposed method applies the fuzzy inference system to determine adjustment coefficients of each pixel for adjusting brightness of the image. Through the processes as mentioned above, we can obtain the result which is adjusted its brightness. To verify the proposed method, we compare the result image with two different images, a reference image, and an adjusted image by using offset. It is confirmed that the proposed method can adjust a given image efficiently and automatically.
Year
Venue
Field
2017
Joint International Conference on Soft Computing and Intelligent Systems SCIS and International Symposium on Advanced Intelligent Systems ISIS
Computer vision,Color space,Computer science,Photography,RGB color model,Pixel,Artificial intelligence,Offset (computer science),Brightness,Fuzzy inference system,Cognitive neuroscience of visual object recognition
DocType
ISSN
Citations 
Conference
2377-6870
1
PageRank 
References 
Authors
0.48
0
4
Name
Order
Citations
PageRank
Eun-Kyeong Kim162.59
Hansoo Lee2106.14
Sungshin Kim321064.17
Hyunhak Cho4184.29