Abstract: n recent past [1]-[2], many neurological disorders diagnosed with the help of eye movement signals. Such type of disorders is reflected through the abnormalities of eye movements. This is why eye movement signals are being utilized for identification of such brain level abnormalities [6]-[11]. The key factor that is associated with such identification is the combined nature of human eye movement plant and brain stem control. For defense personnel, timely identification of neurological disorders plays crucial role in order to prevent the degree of such disorders from mild to severe as they have higher chance for repeated trauma. Further, eye movement biometric features extracted from eye movement signals are being used for such diagnosis due to its intrinsic discrimination properties and associated brain level activity [2]. In this paper, we investigated the mild traumatic brain injury (m-TBI) neurological disorder identification by eye movement biometric through intelligent machine lea

• Publication Date: 29-Aug-2015
• DOI: 10.15224/978-1-63248-073-6-02
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Abstract: Security problems that recently appeared in transmission and storing of digital content can be solved by using watermarking. Reversible watermarking is the election in medical and defense imagery because these security systems are able to restore the original image after extracting the hidden information. In this document an intelligent reversible watermarking scheme is proposed. It is based on the difference expansion method developed by Tian and it is helped by genetic algorithms to improve the imperceptibility of the mark for a fixed payload. Furthermore, it is shown that the image can be divided in blocks watermarking each one, so if an adulteration takes place, it can be determined the block where this happened.

• Publication Date: 29-Aug-2015
• DOI: 10.15224/978-1-63248-073-6-03
• Views: 0
• Downloads: 0