نضال خضير عباس العبادي

Noise is a random variation of image intensity and appear as grains in the image. There are many methods suggested for de-noising.Image de-noising involves the manipulation of the image data to produce a visually high quality image. In this paper we suggested new filterfor de-noise based on simple total least square. The simple total least square is the process of finding the smallest difference between the square of pixel and the square of 8- neighbors pixels. The proposed algorithm tested with (Salt and pepper , Speckle, Gaussian and Poisson noise) with different concentration of noise and gives promised results. Also proposed algorithm compared with other de-noising algorithms and the results were better.

Detection and segmentation of faces from an image is a crucial problem that has gained importance, face detection and segmentation play the main role in the face recognition systems. There are many difficulties should be solved to make the face detection and segmentation algorithm successful. The face skin has special colors range as well as special textures that can be detected by using texture recognition algorithms which recognized skin from the background. In this paper we introduced a new method for face detection and segmentation based on face color, we uses the YCbCr color space as a method to segment image to many regions. Gray level co-occurrence matrix used to extract the important features represent the skin, and then Tamura texture used to remove all the non skin blobs which is recognized as skin by GLCM. The proposed algorithm tested with many images and it was successfully recognize the images with faces from images without faces. The proposed algorithm has high efficient in detected faces and segmented faces from the background. The accuracy of this algorithm more than 99% in detection faces and also segment its. The proposed algorithm forms a prerequisite for any practical verification system using face as the main attribute.

The task of face recognition has been actively researched in recent years because of its many applications in various domains. This study suggested new and novel method to matching the input face image with face images in database based on GSVD. Euclidian distance for the norm of two factors resulted from GSVD of each pair of images was determined. When the distance less or equal to specific threshold we decide the two images matched. The accuracy of this proposed algorithm was high comparing with other algorithms and it reached up to 97. 21%. The algorithm tested with images from ORL database and Indian face database.

Noise is a random variation of image intensity and appear as grains in the image. There are many methods suggested for de-noising. One of them is filtering image by using singular value decomposition, this filter work well but did not remove all the noise in the color image. In this paper we suggested to improve the performance of this filter by combined it with suggested filter based on total least square value. The proposed algorithm tested with (Salt and pepper and Speckle noise) and different concentration of noise and gives promised results. Also proposed algorithm compared with other de-noising algorithms and the results were better.

The security of information exchange is very important on the network. Authentication and information hiding have also become important issues. Information hiding techniques are acquiring an increasing importance due to the widespread diffusion of multimedia contents. The aim of this chapter is to focus on the Singular Value Decomposition (SVD) transform, with the aim of providing an exhaustive overview on those steganography, image cryptography and watermarking techniques leveraging on the important properties of such a transform. Despite the attention it has received in the last years, SVD in image processing and security is still in its infancy. Many SVD characteristics are still unutilized in image processing. In this chapter the author tries to highlight the basic properties of SVD and some of their applications in the field of security to encourage researchers to discover more about SVD properties which are not yet utilized.

In today’s multimedia age, images are becoming more and more common in various fields. Database is an area that has found extensive use of images in past few years. With the increased usage of image data, the need to search and matching images efficiently and accurately from a large image database or a cluster of images databases has increased. Image search has become a popular feature in many search engines, including Google, Yahoo!, MSN, etc., majority of which use very little, if any, image information. In this study we introduced a novel algorithm for searching for image in huge database based on SVD, the proposed algorithm solved some of the other searching algorithms problems, like problems of image scaling, image rotation, search time. The contribution of this algorithm is to retrieve the exact image and/or the image with different view or captured in different time with fixed time regardless the database size, database can be indexed according to the Suggested Values extracted from SVD. The proposed algorithm gives high performance and solved many issues related to other image search algorithms.

Nowadays, text encryption is recommendable when it is transmitted or stored on insecure channels as Internet. In this paper we introduced novel method to encrypt text based on SVD. Up to our knowledge this is the first paper encrypted text by using SVD. The message is the composition of some character. Every character of the message can be represented as an ASCII value, and then we can build numeric matrix for each text. We suggested using other text as key and using with plaintext to scramble the plaintext prior to use the SVD process which makes cryptanalyst’s job difficult. There are many difficulties in using the SVD to encrypt text. The decrypted text was the same as the plaintext without loss any character. Encryption and decryption time were reasonable. One of the important features of this work is the ability to produce encrypted text with language differ from the plaintext language which make add more complixity of decrypt the encrypted text from third party.

Accurate measurement of vessel diameters on retinal images plays an important part in diagnosing cardiovascular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. In this study we develop new method based on computer aided to determine the width of retinal blood vessels by analysing the color fundus image. Retinal vessel diameter was measured based on blood vessel wall estimating on the digital fundus image. We suggested a dependable and accurate technique to determine the diameter (width) of retinal blood vessel based on suggested mask created to use specifically on measuring the blood vessel diameter. The suggested system starts by removing the bifurcations and determine the width for each blood vessel segment. Suggested algorithm tested and gives accurate and promised results.

Automatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. Currently, there is a great interest in the development of Computer-Aided Diagnosis (CAD) systems for dermoscopic images. The segmentation step is one of the most important ones, since its accuracy determines the eventual success or failure of a CAD system. This study introduced new method of dermoscopic images segmentation. The preprocess was the filtering operation to dermoscopy image to remove most of difficulties facing the efficient segmentations, like a variety of lesion shapes, sizes, color, changes due to different skin types and textures and presence of hairs. Segmentation based mainly on histogram thresholding. The enhancements of image achieved by using mathematical morphology in order to obtain better segmentation with smooth border and without any noise in the lesion region. The proposed method evaluated by using Hammoude Distance (HM) and the True Detection Rate (TDR). Also the proposed method is compared with other skin lesions segmentation methods such as Otsu, adaptive thresholding and fuzzy C-means. The accuracy of proposed method was 96.32%, which is highly promised result and dependable.

The growth of digital image and video archives is increasing the need for tools that effectively filter and efficiently search through large amounts of visual data. Towards this goal we suggested new method to automatically extract the color for the image to form a class of meta-data that is easily indexed. The algorithm of indexing the color based on the binary image to extract color regions from image. To achieve this goal the image segmented to many parts after converting color image to binary image based on Y component from the YCbCr color space. Color factors determined for each part by first convert color image for each part to HSV color space and then from the H component define the dominant color for that part. The proposed algorithm tested with many different images and gives very promised results.

Image encryption is one of the most methods of information hiding. A novel secure encryption method for image encryption is presented in this study. The proposed algorithm based on using singular value decomposition SVD. In this study we start to scramble the image data according to suggested keys (two sequence scrambling process with two different keys) to finally create two different matrices. The diagonal matrix from the SVD will be interchanged with the resulted matrices. Another scrambling and diagonal matrices interchange will apply to increase the complexity. The resulted two matrices combine to one matrix according to predefined procedure. The encrypted image is a meaningfull image. The suggested method tested with many images encryption and gives promised results.

There are serious problem for storage sparse matrix due to west of memory used for storage the non-zero values which represent more than 90% of sparse matrix. There are many algorithms suggested for solving this problem. A new storage method for large sparse matrices was presented in this paper based on quadtree. The suggested algorithm utilized the idea of quadtree to re-represent the sparse matrix in two vectors, which reduce the required memory space for storage sparse matrix. The suggested algorithm reduced the memory space required to store the zero values to more than 85%. The algorithm compared with many algorithms and it was more efficient than almost all the previous algorithms up to our knowledge. The current algorithm characterized by less space storage need, highly speed, and easy to implement.

In this study we will provide a new way of images compression based on two mathematic concepts, these two concepts are Singular Value Decomposition (SVD) and Block Truncation Coding. The input image either is in JPEG format or in BMP format and the current way suitable for both color and gray scale images. The input image will be compressed first by reducing the image matrix rank, which achieved by using the SVD process and then the result matrix compressed by using BTC. The proposed algorithm gives further lossless compression to JPEG compression process and the rate of compression reach more than 99%.

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death of female worldwide. Mammogram is one of the most excellent technologies currently being used for diagnosing breast cancer. Computer aided diagnosis helps the radiologists to detect abnormalities earlier than traditional procedures. In this paper, we suggested to use some of features selected to distinguish the benign and malignant breast cancer. Tumor segmented and denoising prior to classification. The accuracy of proposed system was 100%.

Diabetes affects a lot of people everywhere, and has associated complications such as vision loss, heart failure and stroke. Among a group of 100 patients with diabetes, 10 people would likely have diabetes-related eye problems. An ophthalmologist (eye doctor) would have to check the eyes of all 100 patients periodically to find out who had problems. The proposed system tend to analysis the retina fundus images for early detect of any sign related to eyes problems due to diabetic. The image analysis system is broken down into a number of modules which sequentially process the input image to extract information at different levels. These modules included detection the exudates and hemorrhage, blood vessel touristy measure, blood vessel diameter, and each of these modules may need another steps for analyzing of image. The results were highly promised and the percentage of early detection for normal and abnormal retina was 100%.

The bifurcations and crossovers are important feature points, which play important roles in the analysis of the retinal vessel tree. More than 100 vascular bifurcations can be seen in a typical retinal fundus image. Their manual detection by a human observer is a tedious and time consuming process. This paper attempts to automate the detection of retinal vascular bifurcations and crossovers points and removing it from the image. We created a specific mask used to locate and recognize the nodes and crossover points in retinal fundus image. The results of implementing this proposed algorithm was reliable and very accurate.

Vision is the most advanced of our senses, so it is not surprising that images contribute important role in human perception. This is analogous to machine vision such as shape recognition application which is important field nowadays. This paper introduces a new approach for recognizing twodimensional shapes in an image, and also recognizes the shapes type. The algorithm recognizes all the known shapes basis on segmenting images into regions corresponding to individual objects and then determine the shape factor which is use to recognize the shape type. Algorithm tested with many images with different shapes and recognizes all.

Diabetic retinopathy is a major cause of blindness. Earliest signs of diabetic retinopathy are damage of blood vessels in the eye and then formation of lesions in the retina. This paper presents an automated method for detection of bright lesions (exudates) in retinal images. New methods are developed to localize and isolate the optic disk and detect the exudates. A novel algorithm is presented to localize the optic disk and treat the confusion due to similarity between exudates and optic disk. The algorithm use specific color channels and some of image features to separate exudates from physiological features in digital fundus images. The algorithm is tested on many images from published database and gives excellent and promise results.

The retinal vasculature is composed of the arteries and veins with their tributaries which are visible within the retinal image. The segmentation and measurement of the retinal vasculature is of primary interest in the diagnosis and treatment of a number of systemic and ophthalmologic conditions. The accurate segmentation of the retinal blood vessels is often an essential prerequisite step in the identification of retinal anatomy and pathology. In this study, we present an automated approach for blood vessels extraction using mathematical morphology. Two main steps are involved: enhancement operation is applied to the original retinal image in order to remove the noise and increase contrast of retinal blood vessels and morphology operations are employed to extract retinal blood vessels. This operation of segmentation is applied to binary image of top-hat transformation. The result was compared with other algorithms and give better results.

Retinal vascular vessels have the role to indicate the retinal diseases and for systematic diseases when there are any abnormalities in retinal vascular pattern. A characteristic of the vascular pattern that is appreciated by clinicians is vascular tortuosity, i.e., how curved or kinked a blood vessel, either vein or artery, appears along its course. In this study we suggest a novel mask filter to track the blood vessel along its course and measuring the blood vessels tortuosity over the entire human retinal vessel network in fundus eye image, by using the arc to chord ratio. The suggested algorithm tested with straight and curve hand drawing lines and gives high accurate results.

Diabetic Retinopathy is a medical condition where the retina is damaged because fluid leaks from blood vessels into the retina. The presence of hemorrhages in the retina is the earliest symptom of diabetic retinopathy. The number and shape of hemorrhages is used to indicate the severity of the disease. Early automated hemorrhage detection can help reduce the incidence of blindness. This paper introduced new method depending on the hemorrhage shape to detect the dot hemorrhage (DH), its number, and size at early stage, this can be achieved by reducing the retinal image details. Detection and recognize the DH by following three sequential steps, removing the fovea, removing the vasculature and recognize DH by determining the circularity for all the objects in the image, finally determine the shape factor which is related to DH recognition, this stage strengthens the recognition process. The proposed method recognizes and separates all the DH.

With the great convenience of computer graphics and digital imaging, it becomes much easier to alter the content of images than before without any visually traces to catch these manipulations. Many fake images are produced whose content is feigned. Thus, the images cannot be judged whether they are real or not visually. In order to detect fake images, this paper proposes a blind detection uses singular value decomposition (SVD) as a classifier to make a binary decision on whether an image is fake or real. This work is an improvements process to an existence method to detect fake image using SVD. The experimental results prove the effectiveness of this algorithm to detect any small changes in image even with one dot of real image.

Data compression is a common requirement for most of the computerized applications. There are number of data compression algorithms, which are dedicated to compress different data formats. This paper examines lossless data compression algorithm for ECG data by using new method to process the ECG image strip, and compares their performance. We confirming that the proposed strategy exhibits competitive performances compared with the most popular compressors used for ECG compression.

Diabetic retinopathy is a major cause of blindness. Earliest signs of diabetic retinopathy are damage of blood vessels in the eye and then formation of lesions in the retina. This paper presents an automated method for detection of bright lesions (exudates) in retinal images. New methods are developed to localize and isolate the optic disk and detect the exudates. A novel algorithm is presented to localize the optic disk and treat the confusion due to similarity between exudates and optic disk. The algorithm use specific color channels and some of image features to separate exudates from physiological features in digital fundus images. The algorithm is tested on many images from published database and gives excellent and promise results.

This paper develops techniques for discriminating between images which used as steganography cover. Algorithm is based on the hypothesis that a particular message embedding scheme leaves statistical evidence or structure that can be exploited for detection with the aid of proper selection of image features analysis. We pointed out the features of image that should be taken more seriously into account in the design of more successful steganography, weight for each of these features determined by using Analytic Hierarchy Process (AHP) which helps to maximize some of the features and gives weight according to the relation between these features. The proposed algorithm tested by using LSB image steganography, stego-image compared with the origin one which gives the promised results.

الكتاب يحتوي على شرح مفصل للغة البرمة C++ بشكل مبسط وهو يتضمن اثنا عشر فصلا يبتدأ من تعليم البرمجة وينتقل الى البرمجة الكيانية.. الكتاب يحتوي على الكثير من الأمثلة المحلولة التي تساعد على فهم المادة بشكل سهل.. الكتاب من الممكن ان يكون مصدر مهم وسهل للطلبة والأساتذة وكذلك ممكن ان يفيد من يرغب بتعلم البرمجة.. الكتاب كتب بلغة بسيطة مفهومة خالية من التعقيد وبشكل احترافي.. هذا الكتاب يعتبر إضافة للمكتبة العربية التي تفتقد الى كتب علمية مكتوبة باللغة العربية حيث انه كتب من مختص بتدريس لغات البرمجة

Sorting has been a profound area for the algorithmic researchers and many resources are invested to suggest more works for sorting algorithms. For this purpose, many existing sorting algorithms were observed in terms of the efficiency of the algorithmic complexity. Many algorithms are very well known for sorting the unordered lists. In this proposed algorithm, we suggested a new algorithm for sorting integers number depending on dividing the input array to many sub-arrays (which represents a vector or array with one dimension), according to the number of digits in each integer number, the relation between sub-array elements is determined, and this relation used to determines the right location of each element in subarrays. Collision may happen, which is solved by moving elements in sub-array to next location. Finally, all ordered sub-arrays will be merged together to rebuild the origin array. The proposed algorithm compared with many famous algorithms gives promising results.

There are many known Arabic lexicons organized on different ways, each of them has a different number of Arabic words according to its organization way. This paper has used mathematical relations to count a number of Arabic words, which proofs the number of Arabic words presented by Al Farahidy. The paper also presents new way to build an electronic Arabic lexicon by using a hash function that converts each word (as input) to correspond a unique integer number (as output), these integer numbers will be used as an index to a lexicon entry.

In this study a skin disease diagnosis system was developed and tested. The system was used for diagnosis of psoriases skin disease. Approach: Present study relied on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin diseases. We used feed forward neural networks to classify input images to be psoriases infected or non psoriasis infected. Results: The system gave very encouraging results during the neural network training and generalization face. Conclusion: The aim of this worked to evaluate the ability of the proposed skin texture recognition algorithm to discriminate between healthy and infected skins and we took the psoriasis disease as example.

كتاب يحتوي على العديد من الفصول التي تهتم بتقديم المعلومات عن كيفية البرمجة باستخدام لغة البرمجة باسكال, الكتاب من الممكن ان يكون مفيد للمبتدئين وللمختصين وقد تم تعزيز الشروحات بامثلة متعددة.