Dr. Awad Al-Asmari

King Saud University Saudi Arabia

Awad Kh. Al-Asmari was born in Balasmer, Saudi Arabia in 1959. He received his B.Sc and M.Eng from King Saud University, Riyadh, Kingdom of Saudi Arabia and Ohio State University, Columbus, Ohio, U.S.A, respectively. He then proceeded to the University of Toledo, Toledo, Ohio, U.S.A. where he obtained his PhD in 1991 specialising in communication and signal processing. Since 1991 he has been a faculty member at the College of Engineering, King Saud University, Saudi Arabia, where he rose through the ranks to become a full professor in 2003. In addition to this, he was appointed Vice Rector for Graduate Studies and Research at the Salman Bin Abdulaziz University, Kharj, in 2009. Prof Awad Alasmari is deeply involved in numerous services to his immediate constituencies, both geographical and professional. He has been a senior member of the IEEE since 1996 and has co-authored numerous publications in the areas of image processing, information security, telecommunications, nanotechnology and quantum computing. He can be reached at www.alasmari.com.

Dr. Awad Al-Asmari

1books edited

3chapters authored

Latest work with IntechOpen by Dr. Awad Al-Asmari

Discrete Wavelet Transform is a wavelet (DWT) transform that is widely used in numerical and functional analysis. Its key advantage over more traditional transforms, such as the Fourier transform, lies in its ability to offer temporal resolution, i.e. it captures both frequency and location (or time) information. This book presents a succinct compendium of some of the more recent variants of DWTs and their use to come up with solutions to an array of problems transcending the traditional application areas of image/video processing and security to the relatively newer areas of medicine, artificial intelligence, power systems and telecommunications. The first of the two sections of this book contains three chapters devoted to traditional applications of DWTs in digital image compression, copyright protection and video resolution enhancement. The second section, comprising of five chapters, is devoted to variants of the DWT and their applications in humanoid-robot vision systems; modeling and simulation recognition of physiological and behavioral traits through human gait and facial images; assessment of agitation and sedation in intensive care patients; maximization of power control systems; and, finally, in demodulation of FM data in free-space optical control systems.

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