The influence of photo elements on EEG signal recognition

• Published in: EURASIP journal on image and video processing Vol. 2018; no. 1; pp. 1 - 9
• Main Authors: Wang, Qingjun, Li, Yibo, Liu, Xueping
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 04.12.2018; Springer Nature B.V; SpringerOpen
• Subjects: Biometrics; Classification; Color; EEG signals; Electrodes; Electroencephalography; Engineering; Identification; Image Processing and Computer Vision; Pattern Recognition; Photo attributes; Photos; Recognition; Signal,Image and Speech Processing; Visual Information Learning and Analytics on Cross-Media Big Data; Photos; Photo attributes; Identification; EEG signals
• ISSN: 1687-5281; 1687-5176; 1687-5281
• DOI: 10.1186/s13640-018-0367-6

With the increasing demand for confidentiality of information, traditional identification tools are no longer sufficient. As a new biological signal, EEG signal has the advantage of being difficult to forge and easy to carry and has become a hot topic in the identification research. In the study of EEG signals, the EEG signals triggered by vision have the advantage of stable characteristics. Therefore, many researchers use the photos of the subjects themselves as stimuli to achieve identification research, but the EEG signals caused by vision are easily stimulated. Object interference, such as photo size, resolution, and color. The main purpose of this paper is to study the effect of these disturbances on the recognition effect. The results show that when the number of electrodes is increased to 9, the effect of increasing the electrode to improve the classification accuracy is not significant; the recognition effect of black-and-white photos is lower than that of color, the size of the picture is 800 × 600 or 1024 × 768. When the resolution is 72, the classification effect is the optimal.