ali abdulazeez mohammed baqer Qazzaz

In this paper, fusion method using wavelet transform was used to calculate the effects of multiple sources of light to make the object look more realistic and more informative than the original parts which take the effect of each light source alone. The color value of any pixel in the object depends essentially on the color of the specific mapped texture as well as on the effect of the light sources that produce bright or dark pixels value depending on the distance between the pixel and light source and the direction of light rays. The proposed method merges the effect of multiple lights

With the fast progression of using images in many applications, it is important to protect the confidential image data from unauthorized access. In this paper we suggested a new way to encrypt image based on three main steps: the first one aims to scrambling the image values by using Fibonacci transform, while the second step focus on generating public and private key based on Diffie-Hellman Key Exchange, these keys used to encrypt the diagonal matrix which created by Singular Value Decomposition (SVD) in third step. Decryption is the inverse process of encryption.

. 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 detec9ted faces and segmented faces from the background.

In this paper, a new method will be introduced for hiding information in images by using a public key method for ciphering the text before hiding information as well as this public key will be used in determining the position where the information will be hidden by using the last position in finding the new position, symmetric key also will be used in hiding process for deciding the number of bits that will be used from each pixel in the image, the combination of steganography and cryptography provide much strong method for keeping information secured and undiscovered from unwanted persons

Performance evaluation and quality metrics is one of the most important parts of producing reliable searches with acceptable results according to real and effective features that will be extracted from the comparison between input and output data in some techniques or from input data only. Many metrics proposed during past years, each of them have its strong sides in some applications as well as some degrade sides in other applications. From other sides there are many various types of data, each of them has its strong metrics, so the metrics become very large scale groups of different gender. This paper presents some of the performance evaluation metrics and the famous usage of each one, as well as some advantages, disadvantages and important aspect of them. The methodology of this paper works by classifying these metrics according to some presented features such as single result to evaluate its accuracy or many results to select the best one of them, type of date where the common data usage in image processing is image while these data is text in encryption algorithms. Objective techniques for suggesting specific value for representing the quality of decided image have tried to attempted to weight the quantity of specific image according to comparison it with a reference image using a variety of accepted properties of the visual system of the human.

Due to the advancement in technology at last years and increasing in the number of cars in the roads, it is necessary to develop techniques and algorithms for detection cars and performing some related tasks like identification the type of each car in the image . This research perform three important tasks, the first one related to discovering the existence of car in the specific image, the second task related to the classification process of cars into pre decided classes, and the third one related to discovering the direction of the car into (front, rear and side) for the purpose of treatment the presence of several non-accepted actions in the street. The proposed system use the network YOLO-v5 algorithm for performing the proposed tasks, where the data acquired by using suitable camera for cars in the streets of Iraq country, which were pre-classified into five classes (personal cars, taxi cars, minibus cars, trucks, and tuk-tuk). The number of acquired images is (7500) images. The training was conducted in the environment of https://colab.research.google.com/, where the results after training on 100 EPOCH were Odds Ratio mAP @ 0.924.

Hiding information either by steganography or watermarking operation is essential for computer science. It is used as a method for sending secure and important information. It has special features that even if this information is discovered, the third part cannot reconstruct the original information in any way, not famously and commonly nor difficultly and especially by using any technique or algorithm. There are many hiding techniques; each one of them used different paths to ensure standard properties such as optimizing security level, increasing the amount of embedding data, decreasing the ability to reconstruct hidden information by any unwanted part. Here in the following suggested technique, different quantities of bits are hidden in various pixels depending on some discovered constraints by using the famous Gabor filter then divided ridges part in a selected fingerprint image for the purpose of hiding relevant information into important and non-important pixels that laying out of ridges in final images after applying Gabor filter which consider not important regions in fingerprint image for discovering important features from the image. The pixels used in hiding information belong to finger ridges in pure fingerprint images but covert to white pixels (valley) in the matrix after applying the Gabor filter and in original white pixels in both matrices by using different techniques for each type of pixels. The imaging stage constructed after the suggested technique is good and identical to the pure image for the accepted degree as shown in used fidelity metrics (PSNR). It is similar to a pure fingerprint matrix as proved in these metrics for calculating the level of goodness of proposed algorithms. Our algorithm exploits existing pixels in fingerprint image with different levels of importance and avoids pixels with high importance for protected important features from non-deterministic varying.