F. E. Abd El-Samie

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This paper presents two innovative techniques developed and implemented for the automation of the landmine detection in a data scanned by the laser Doppler vibrometer (LDV) based acoustic to seismic (A/S) landmine detection system. These techniques are based on the intensity component of the color landmine images or on grayscale versions of these images.(More)
This paper proposes a simplified fractal image compression algorithm which is implemented on a block by block basis. This algorithm achieves a compression ratio of up to 10 with a peak signal to noise ratio (PSNR) as high as 35 dB. The idea of the proposed algorithm is based on the segmentation of the image, first, into blocks to setup reference blocks. The(More)
This paper introduces a cepstral approach for the detection of landmines from acoustic images. This approach is based on transforming the 2D landmine images to 1D signals using a spiral scan to make object pixels as close as possible to each other after the scan. The Mel-frequency cepstral coefficients (MFCCs) and polynomial shape coefficients are extracted(More)
This paper deals with the problem of blind separation of denoising. It proposes the application of the discrete wavelet transform as a preprocessing step of denoising prior to the blind separation algorithm. The separation of sinusoidal signals as well as speech signals in a noisy environment is studied with and without the use of the wavelet denoising(More)
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