Mohamed M. Fouad

Work place: Computer Engineering Department at MTC, Cairo, Egypt.



Research Interests: Information Retrieval, Speech Recognition, Image and Sound Processing, Pattern Recognition, Graph and Image Processing, Handwritten Recognition


Mohamed M. Fouad, received the Bachelor engineering (honors, with great distinction) and Masters' engineering degrees from the Military Technical College (MTC), Cairo, Egypt, in 1996 and 2001, respectively. As well, he received the Ph.D. degree in Electrical and Computer engineering from Carleton University, Ottawa, Ontario, Canada, in 2010. Received the PhD degree from the department of Systems and Computer Engineering at Carleton University in Canada in Nov. 2010. He has been promoted to Associate Professor in March 2016. He has been promoted to IEEE Senior Member in April 2019. He is currently the Head of Computer Eng. & A.I. Dept, M.T.C., Cairo, Egypt since January 2018. His research interests are in online handwritten recognition, image registration, image reconstruction, image retrieval, super-resolution, video compression, and multiview video coding.



Author Articles
Lossless Image Compression Using A Simplified MED Algorithm with Integer Wavelet Transform

By Mohamed M. Fouad Richard M. Dansereau

DOI:, Pub. Date: 8 Nov. 2013

In this paper, we propose a lossless (LS) image compression technique combining a prediction step with the integer wavelet transform. The prediction step proposed in this technique is a simplified version of the median edge detector algorithm used with JPEG-LS. First, the image is transformed using the prediction step and a difference image is obtained. The difference image goes through an integer wavelet transform and the transform coefficients are used in the lossless codeword assignment. The algorithm is simple and test results show that it yields higher compression ratios than competing techniques. Computational cost is also kept close to competing techniques.

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Content-based Search for Image Retrieval

By Mohamed M. Fouad

DOI:, Pub. Date: 8 Sep. 2013

In this paper, a content-based image retrieval approach is presented for effective searching. The proposed approach uses two or more types of query for accessing images, textual annotation associated with images and visual appearance, such as colour, texture and positional features of objects in sample images. One can first place a keyword-based query, and then the desired images are retrieved by visual content-based query. The proposed retrieval approach shows clear improvements over competing approaches in terms of retrieval accuracy and visual inspection using Corel gallery and WWW images. 

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Other Articles