Digital Image Processing

Sahar Aboshosha , O. Zahran ¹, M. El-Kordy ², F. E. Abd El-Samie ³

Affiliations
1 Electronics and Electrical Communications Department, Menoufia University, Menouf, EG
2 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG
3 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG

Abstract

In this paper histogram equalization with image interpolation are presented. Histogram equalization is a very important widely used contrast-enhancement technique in image processing. Image enhancement is a means of improvement of an image appearance by increasing luminance of some a distinctive attribute or by decreasing ambiguity between different regions of the image to improve quality. This paper proposes simultaneous interpolation and equalization of digital images. The best performance has been achieved when performing the equalization on interpolated images instead of performing the interpolation on equalized images. Finally, we can say that the proposed techniques achieve better performance compared to other techniques. 

Keywords

Histogram Equalization, Interpolation, and Image Enhancement.

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E. M. El-Bakary ¹, O. Zahran ², S. El-Rabaie ³, F. E. Abd El-Samie ⁴

Affiliations
1 Department of Electronics and Electrical Communications, Menoufia University, 32952, Menouf, EG
2 University of Liverpool, GB
3 Menoufia University, EG
4 Electrical Communications, Menoufia University, EG

Abstract

Video is compressed to move the redundancies for efficient communication. In this paper, we use a steganography method for verification of the video content at the receiver side. The main idea of the proposed steganography method is based on the Discrete Cosine Transform (DCT). It is based on creating a signature for each block of the DCT of the compressed video sequence to be embedded in another block. This is attributed to the fact that most DCT coefficients of the compressed video sequence are either zero or close to zero. Simulation results reveal the robustness of the suggested steganography method.

Keywords

Video Compression, Data Hiding, Steganography.

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Mohsen A. M. El-Bendary ¹, H. Abdellatif ², M. El-Tokgy ², T. E. Taha ², Sayed M. EL-Rabaie ², O. F. Zahran ², W. Al-Nauimy ³, Saleh Ahmad ², F. E. Abd El-Samie ²

Affiliations
1 Department of Electronics Technology, Helwan University, Cairo, EG
2 Menofia University, EG
3 Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, L693GJ, Liverpool, GB

Abstract

Mammography is well known method for detection of breast tumors. Early detection and removal of the primary tumor is an essential and effective method to enhance survival rate and reduce mortality. Breast tumor segmentation is needed for monitoring and quantifying breast cancer. However, automated tumor segmentation in mammograms poses many challenges with regard to characteristics of an image. In this paper we propose a fully automatic algorithm for segmentation of a breast masses, using two types of image segmentation, Normalized graph cuts to delineate pectoral muscle and optimal threshold based on the two-dimensional entropy for masses detection.

Keywords

Mammography, Image Segmentation, Thresholding, Entropy, Normalized Graph Cuts.

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E. M. El-Bakary ¹, O. Zahran ², S. El-Rabaie ¹, F. E. Abd El-Samie ³

Affiliations
1 Department of Electronics and Electrical Communications Engineering, Menoufia University, Menouf-32952, EG
2 Department of Electronics and Electrical Communications Engineering, Menoufia University, Menouf-32952, EG
3 Department of Electronics and Electrical Communications Engineering, Menoufia University, Menouf-32952, EG

Abstract

The videois compressed to move the redundancies for reducing the number of bits whichneed to show the video for reducing the size of video to reduce the band width. We embed the hiding data in redundancies of the video frame withoutvisibility manner using Steganography technique. In our research we focus in increasing the improvement of compressed video frame through using steganography. In our research we use two mixed techniques to compress the video, the first is digital steganography and the second is data compression. Hence, the suggested scheme is mixed the algorithm ofthe steganography algorithm with the DCT compressionvideo frame.The suggested scheme in our study compression of data is made in two steps. In the first step,redundant data isminimized by compaction of energy using video. In the second step, with using steganography bit blocks isembedded in its blocks which call subsequent of the same video frame. Theadvantage of thebits which it is embedded isdecrease the size of the file and increase thesize of the file of the compressed video frame, but also decrease the file size further more. Theresults of simulation results explainthat,the suggestedschemehave more potential in coding of the frame of the video.

Keywords

Video, Data Hiding and Compression and Steganography, DCT Compression.

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Hayam A. Abd El-Hameed ¹, Emad S. Hassan ², Sami A. El-Dolil ², F. E. Abd El-Samie ²

Affiliations
1 Dept. of Electronics and Electrical Comm., Menoufia Univ.,32952, Menouf, EG
2 Dept. of Electronics and Electrical Comm., Menoufia Univ.,32952, Menouf, EG

Abstract

Since all the multimedia products are released via internet so it‟s very important need today to protect the data from malicious attacks. This directs us to look at digital watermarking which intends to protect the copyright information of the users. This paper presents a Discrete Cosine Transform (DCT) based Signature scheme which provides higher resistance to image processing attacks such as speakle noise, rotation, Gaussian, etc. The invasive distribution of digital images and the growing concern on their integrity and originality in need of authenticating corrupted images by transmission. To meet this need, this paper proposes a new technique that is make digital signatures in image robust to image degradations. The DCT is used to improve the security against forgery attacks due to its precise localization properties and excellent multiscale. Several experiments are carried out to test the proposed scheme in terms of Peak Signal to Noise Ratio (PSNR) and Normalized Cross-Correlation (NC).The obtained results confirm that the proposed scheme can achieve good efficiency against transmission errors. It also is very robust to counterfeiting attacks.

Keywords

Discrete Cosine Transform (DCT), Signature, Attacks, Normalized Cross-Correlation (NC).

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E. A. El-Shazly ¹, O. Zahran ², S. M. Elaraby ¹, M. El-Kordy ², F. E. Abd El-Samie ²

Affiliations
1 Engineering Department, Nuclear Research Center, Atomic Energy Authority, Cairo, EG
2 Electrical Communications Department, Menoufia University, Menouf, EG

Abstract

In this paper new identification techniques for buried landmine objects are presented.  Most of the existing supervised identification methods are based on traditional statistics, which can provide ideal results when sample size is tending to infinity. However, only finite samples can be acquired in practice. In this paper, two proposed learning methods; Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), are applied on landmine images. The complete identification technique consists of two stages to perform both the training of the input image models and the evaluation of the testing image sets. In the 1st stage, the 2-D images are transformed into 1-D signals by a spiral scan, and then the Mel Frequency Cepstral Coefficients (MFCCs) and polynomial coefficients are extracted from these 1-D signals and/or their transforms. In the 2nd stage, the ANN and SVM are used to match the extracted features in the testing phase to those of the training phase. Experimental results have shown that the proposed techniques are effective with landmines. The best performance has been achieved with features extracted from the Discrete Cosine Transform (DCT) signals using ANN and from the DCT of images contaminated by AWGN and speckle noise and from the Discrete Sine Transform (DST) of images contaminated by impulsive noise using SVM. Finally, we can say that the proposed techniques achieve better performance compared to other techniques.

Keywords

Spiral Scan, Landmines Identification, ANNs, SVMs, MFCC, Kernel Functions.

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A. A. Mahmoud ¹, S. EL. Rabaie ², T. E. Taha ², F. E. Abd El-Samie ³, O. Zahran ², W. Al-Nauimy ⁴

Affiliations
1 Department of Electronics and Electrical Communications, Menoufia University, 32952, Menouf, EG
2 Department of Electronics and Electrical Communications, Menoufia University, 32952, Menouf, EG
3 Department of Electronics and Electrical Communications, Menoufia University, 32952, Menouf, EG
4 University of Liverpool, GB

Abstract

Image denoising involves processing of the image data to produce a visually high quality image. The denoising algorithms may be classified into two categories, spatial filtering algorithms (Wiener filter, Gaussian filter, Gabor filter and Median filter) and wavelet based algorithms (Wiener filter in the wavelet domain and Log Gabor filter in the wavelet domain). In this paper a comparative study for the previous mentioned algorithms based on calculating the Peak Signal to Noise Ratio (PSNR) value as a metric since for such images the visual evaluation is not appropriate. The quantitative results of comparison are tabulated by calculating the PSNR of the output image.

Keywords

PSNR, DWT.

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