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Composite Techniques Based Color Image Compression
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Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3 rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM) in M technique which has the highest values of energy (En) and compression ratio (CR) and least values of bit per pixel (bpp), time (T) and rate distortion (R (D)). Also the values of the compression parameters of the color image are nearly the same as the average values of the compression parameters of the three bands of the same image.

Publication Date
Fri Jan 01 2016
Journal Name
Bio-inspired Computing – Theories And Applications
Image Segmentation Using Membrane Computing: A Literature Survey
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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding text in gray image using mapping technique
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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes On Data Engineering And Communications Technologies
Utilizing Deep Learning Technique for Arabic Image Captioning
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Publication Date
Sun Jan 01 2023
Journal Name
Proceedings Of International Conference On Data Science And Applications
Very Low Illumination Image Enhancement via Lightness Mapping
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Publication Date
Tue Jun 01 2021
Journal Name
Al-nahrain Journal Of Science
Medical Image Denoising Via Matrix Norm Minimization Problems
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This paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given ma

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Publication Date
Fri Aug 05 2016
Journal Name
International Journal Of Advances In Scientific Research And Engineering
Image Encryption Using Modified AES with Bio-Chaotic
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Due to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.

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Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Spin-Image Descriptors for Text-Independent Speaker Recognition
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Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for Facial Image Detection System
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HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

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Publication Date
Wed Aug 20 2025
Journal Name
Al–bahith Al–a'alami
Organizational reputation: A descriptive study of concept development and measurement techniques
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The study aimed to monitor the concept of reputation in the previous literature, its relationship to mental image and identity, and to reveal recent trends in its measurement Techniques.

    The study relied on a descriptive approach using library survey and comparative analysis, and the study reached following conclusions:

     Despite the beginning of the first signs of reputation In the fifties of the last century, however, Defining and standardizing the concept with clear and specific dimensions began in the 1990s and the beginning of the third millennium. The concept of reputation refers to the stakeholders’ overall evaluation of organizations, which reflects their perceptions of

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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