"Novel Approach to Personal Identification Based on Eye Movements for Recognition and Security Applications"
New research explores the application of deep learning to analyze spectrogram images of the human eye and its movements as a biometric tool. For recognition and security applications, a group of researchers has created a novel method of personal identification based on eye movements. Since it focuses on the involuntary nature of certain eye movements, the biometric technique has proven resistant to fraudulent attempts. The team reached an accuracy of about 73 percent for eye angle spectrogram identification, and 65 percent for eye coordinate spectrogram identification testing. Together, this would be effective at identifying an individual based on their unique pattern of eye movements. According to the team, this is the first time spectrograms have been used in this way. This article continues to discuss the team's personal identification method based on eye movements for recognition and security applications.
Submitted by grigby1