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Medical images typically have diagnostic and confidential data and information about the patient and are usually sent using public networks. Due to the sensitivity of medical images, their security has become a challenging requirement that must be addressed. Traditional cryptographical algorithms are inadequate to ensure appropriate and fine security while encrypting them, because of the correlation between each pixel, high redundancy of the image and its major size. Chaotic systems with their properties and partial encryption based on frequency domain are the best candidates for securing the storage and transfer of digital images. The paper shows new criteria for encryption of medical image. It is designed to improve performance and meet the increasing need for better security for medical image encryption. At first, the pixel's correlation is eliminated by scrambling the input image and diffusing them using secret sharing based on polynomials. Various frequency domains of the image are accomplished by applying the integer wavelet transform of the scrambled image, namely, the associated detail of (HL, LH and HH) and the LL (approximation coefficient) through using the AES algorithm. The (LL) part is encrypted to originate the diffusion image and by using the inverse of the Haar wavelet transform to produce a reliable, unbreakable and secure form. The designed algorithm is used to reverse and shuffle every frequency sign of the transformed image before transformation image back to the pixel domain. The original image form is restored through the reverse decryption algorithm. The suggested algorithm is measured and evaluated in a statistical way and normal standard security; The outcome of the proposed algorithm shows a strong resistant to the familiar attacks and extra secure than the other algorithms in the domain of image cryptography.

The progressive development in telecommunication and networking technologies has led to the increased popularity of telemedicine usage, which involves the storage and transfer of medical images and related information. Recently, trust and privacy in the telemedicine system have attracted many researchers to investigate these topics. In medical image applications, selective image encryption plays an important role as it reduces computational cost and time. Therefore, a safe and efficient selective image encryption algorithm is designed in this work. In particular, the predetermined region of the original image data is encrypted to reduce the encryption/decryption time and the computational complexity of processing the huge image data. The image processing techniques are used to divide the image into a region of interest (ROI) and a region of non-interest (RONI), and then the more important component of the ROI is encrypted using a polynomial-based secret image sharing (SIS) and a chaotic map system. These techniques produce a test image cipher that has good confusion and diffusion properties. The experimental result shows that the Polynomial-based SIS and the chaotic image encryption are effectively performed for diffusion and confusion, which are crucial for concealment. According to the security research findings, sensitive encryption and decryption systems are extremely reliant on any improvement in the key. The encryption solution is sufficiently broad to withstand brute force attacks. Thus, protection may become an issue during the transmission of medical images via a network.

حماية البيانات مهمه في المجال الطبي حيث انه عند الترويج لتطبيقات الطب عن بعد ,من الضروري حماية بيانات المريض والمعلومات الشخصية .هناك حاجه الى اليه قوية وامنة لنقل الصور الطبية عبر الانترنت .يقترح في هذه الورقة خوارزمية التجزئه لحماية البيانات باستخدام ميزات قوية من نطاقات التردد المقترنه لتحويل(SLT)وتحويل جيب التمام المنفصل (DCT).تتم ترجمة منطقة الاهتمام (ROI) من صورة التصوير بالرنين المغناطيسي ثم يتم استخراج مجموعة الميزات لحساب رمز التجزئه .اخيرا ,يتم تشفير كود التجزئه للحفاظ على الامان من خلال استخدام مفتاح التحول الفوضوي الامن .يتم ضمان طريقة الامان المقترحة من خلال قوة CSK وسرية مفتاحالتشفير . تم اجراء تحليل مفصل باستخدام 1000صوره غير مضغوطه تم اختيارها عشوائيا من قاعدة بيانات AANLIB المتاحة للجمهور . طريقة التجزئه المقترحة قوية لضغط JPEG .تقاوم هذة الطريقه ايضا العديد من هجمات معالجة الصور مثل التصفية واضافة الضوضاء وبعض التحويلات الهندسية .

Iris recognition indicates the procedure of recognizing humans based on their both left and right iris patterns. Nowadays there is rapid progress in realizing an old dream of developing a user-friendly recognition system. Most of the new projects became a nightmare of security of the system. The prosperity of iris recognition aside from its attractive physical characteristics is led to developing an efficient feature extractor to attain the required objective of recognition. Fingerprint, facial, and iris biometric techniques are developed widely for identifying processing most boarded management points, access control, and military checkpoints. Hybridization between Daugman’s Integro Differential Operator (IDO) with edge base methods was realized through taking the advantages of the good qualities of both methods so as to enhance the precision and reduce the required time. The proposed hybrid recognition system is very reliable and accurate. UBIRIS version 1 dataset was utilized in the conducted simulation which indicates the distinctions of the hybrid method in providing good performance and accuracy with reducing the time consuming of iris localization by approximately 99% compared with IDO and edge based methods.

This paper introduces an effective image encryption approach that merges a chaotic map and polynomial with a block cipher. According to this scheme, there are three levels of encryption. In the first level, pixel positions of the image are scuffled into blocks randomly based on a chaotic map. In the second level, the polynomials are constructed by taking N unused pixels from the permuted blocks as polynomial coefficients. Finally, the third level a proposed secret-key block cipher called extended of tiny encryption algorithm (ETEA) is used. The proposed ETEA algorithm increased the block size from 64-bit to 256-bit by using F-function in type three Feistel network design. The key schedule generation is very straightforward through admixture the entire major subjects in the identical manner for every round. The proposed ETEA algorithm is word-oriented, where wholly internal operations are executed on words of 32 bits. So, it is possible to efficiently implement the proposed algorithm on smart cards. The results of the experimental demonstration that the proposed encryption algorithm for all methods are efficient and have high security features through statistical analysis using histograms, correlation, entropy, randomness tests, and the avalanche effect.

The localization of the iris is the most significant factor in biometrics of the iris, which traditionally assumes strictly controlled environments. The proposed method includes the pupillary and limbic iris boundaries localization. A primary advantage of image arithmetic operations is that the process is straightforward and therefore fast, these characteristics are employed and combined with the morphological operators in the designing of the proposed algorithm. The proposed algorithm takes into account the noise area which is found in various parts of the eye image such as light reflections, focus, and small visible iris. The experimental results are conducted on a collection of iris images consist of 756 images belong to Chinese Academy of Sciences Institute of Automation (CASIA V-1) and 450 images belong to Multi Media University (MMU V-1) databases. The results indicate a high level of accuracy using the proposed technique. Moreover, the comparison results with the state-of-the-art iris localization algorithms expose considerable improvement in segmentation accuracy while being computationally more efficient.

Primary challenges are the identification, segmentation, and extraction of the afflicted area from the scanning of magnetic resonance. However, it is a time-consuming and tiresome for clinical specialists. In this paper, an automated brain tumor system is proposed. The proposed system employs hybrid image processing techniques such as contrast correction, histogram normalization, thresholding techniques, arithmetic, and morphological operations to quarantine nearby organs and other tissue from the brain for improving the localization of the affected region. At first, the skull stripping process is proposed to segregate the non-designated regions to extract the designated brain regions. Those resultant brain region images are further subjected to discover the brain tumor. The planned scheme is studied on the magnetic resonance (MR) images with the use of T1, T2, T1c, and fluid-attenuated inversion recovery (FLAIR). The proposed hybrid method employed. The results reveal that the proposed method is quite efficient to extract the tumor region. The accuracy rate for segmentation and separation of area of interest in brain tumor reached to 95%. Finally, the significance of the proposed procedure is confirmed using the real image clinical dataset got from ten patients were diagnosed as begin, malignant, and metastatic brain tumors in Al-Yarmouk and Baghdad teaching hospital in Baghdad, Iraq.

This paper attempts to build up a simple, strong and secure cryptographic algorithm. The result of such an attempt is “RC6-Cascade” which is 320-bits RC6 like block cipher. The key can be any length up to 256 bytes. It is a secret-key block cipher with precise characteristics of RC6 algorithm using another overall structure design. In RC6-Cascade, cascading of F-functions will be used instead of rounds. Moreover, the paper investigates a hardware design to efficiently implement the proposed RC6-Cascade block cipher core on field programmable gate array (FPGA). An efficient compact iterative architecture will be designed for the F-function of the above algorithm. The goal is to design a more secure algorithm and present a very fast encryption core for low cost and small size applications.

Background/Objectives: To build a secure multiple secret image sharing system using multiple levels of security. Methods/Analysis: In this paper a multiple secret image sharing based on linear system has been proposed which is performed (k, n) threshold scheme. The proposed system has been used a serial of security techniques to enhance security and reduce storage space to the generated shares. Firstly, the inputs images have been compressed to an attempt to minimize data loss without highly affect the image quality. Secondly, design a 64-bit random number generator by employing the RC5 encryption algorithm round functions with some changes in the usage of the key, where two keys have been used and an initial vector to start the sequence generator. Finally, a developing multiple image secret sharing has been used to generate shares. Finding: The developed sharing technique depends on a set of linear equations mixed with modular algebra where n shares have been generated from secure input images, and gathering more than k shares can be recover these secret images. The experimental results showed that the generated shares are more secure and unrelated. Also the results showed that the size of shares have been reduced to more than 1/4k of total sizes of all combined images. And the proposed diffuser flattens the histogram of every simple tested by it, and that proves the efficiency of it to work on every possible input. The overall execution time of the system is inacceptable range. Application/Improvements: The secret sharing scheme is an advanced cryptography branch that plays crucial role in defense passively, and it would be used to protect valuable or classified information and documents against dangers like robbery and illegal accesses. The improvement was the adding of multiple secret images instead of using one secret at a time.

Image security is essential, topic through the increase of the image usage in most of communications besides assures information security which is hidden in these images such as military and medical images. Blowfish is outstanding symmetric cryptography, which has the benefits of strong ability to resist attackers. Thus it is widely used in data encryption, but it is not suitable for image encryption because of the huge data, higher redundancy and toughly correlation of image pixels. The proposed enhanced method has been employed Blowfish based image encryption technique. Firstly the digital image is decomposed into several key-based blocks randomly to decorrelated the relationship between original and processed image then each block is passed through the Blowfish algorithm. The proposed system is designed to take advantage of the powerful facility, which is supported by a chaotic map resulting in a much-improved security/performance trade-off. As a result, the proposed system offers good performance for image encryption. To ensure improved Blowfish encryption algorithm, the implementation of both techniques has been carried out for experimental purposes which are showed that the original image has a flat histogram after encrypted, a decreasing correlation between adjacent pixels in all colour components and increasing entropy for the cases studied. A comparative study with previous Blowfish algorithm shows the superiority of the modified algorithm.

Patient privacy and image protection is an obligation. Data privacy, data protection, and security must be provided by using encryption to ensure confidentiality. Currently, there are numerous standard traditional encryption algorithms. Most of these are suitable for a text file. It is challenging to employ these algorithms for images or videos directly because of strong adjacent pixels correlations. Decreasing the correlation among the surrounding pixels reduces the detail. An algorithm based on a quadratic map is applied as a preprocessing step to nullify the relationship between pixels and reduce the entropy. The AES image encryption is performed for confusion and diffusion, which are necessary for confidentiality. The security analysis findings indicate that the sensitive encryption and decryption techniques are highly dependent on any improvement in the key. The encryption solution is broad enough to avoid brute-force attacks. Thus, during the transfer of medical images over the network, protection can become an issue.

Medical images are transmitted to other remote places through the E-healthcare system. The protection of medical images is very crucial. Medical images need to be protected against any modification which the attacker may do through the unsecured channel. It is necessary for inspecting the integrity of the ROI (Region of Interest) of the received medical image prior to the adoption of any diagnostic decision to avoid a misdiagnosis. This paper aimed to confirm the integrity and authenticity of medical images by combining the hash signature with the watermarking technique based on the frequency domains. At first, the medical image is divided into ROI and RONI (Region of Non-Interest). The SLT and DCT transformations are employed together to extract the essential features set from ROI and then combined with EPR (Electronic Patient Registration) to produce a watermark, and then it is encoded by a chaotic map with a secret key to provide a signature. On the other hand, the RONI is mapping into randomly subblocks based on the linear system, and then the Signature is embedded in the chosen block using DWT. The hash code of the recovered image and EPR will be compared with the extracted watermark for integrity and authenticity. The experimental results demonstrate the watermark’s robustness against many of the more aggressive and geometric signal processing distortions without affecting the quality of the original medical image. In particular, compared with state-of-the-art technology, the proposed algorithm improves the average NC value larger than 0.90 under all types of attacks.

In order to improve the security and efficiency of image encryption systems comprehensively an image encryption based on enhanced design of Blowfish scheme is proposed. The proposed system is employed block based image encryption technique combined with chaotic map properties. Firstly the digital image is scrambled and decomposed into several key based blocks randomly to decorrelated the relationship between original and processed image then each block is passed through an enhanced blowfish algorithm. The enhancement in design is to gain advantage of the strong facility, which is maintained by blowfish algorithm by overcoming its flaws, which leads to a significant improvement in security/performance. As a result the proposed system offers good performance for image encryption. The proposed algorithm is 320-bit Blowfish-like block cipher, where cascaded looking composition of F-functions is used instead of rounds. The key is accepted a variable length up to 400 bytes. The pragmatic aim of the proposed system is to decrease memory requirements and execution time while keeping the cipher simple and highly adaptable to future demands. To ensure improved encryption algorithm, the implementation of both techniques has been carried out for experimental purposes which is showed that the original image has a flat histogram after encrypted, a decreasing correlation between adjacent pixels in all color components and increasing entropy for the cases studied. The proposed algorithm has a sufficiently large key space and a very high sensitivity to the key. A comparative study with previous Blowfish algorithm shows the superiority of the modified algorithm.

In order to protect valuable data from undesirable readers or against illegal reproduction and modifications, there have been various data encryption techniques. Many methods are developed to perform image encryption. The use of chaotic map for image encryption is very effective, since it increase the security, due to its random behavior. The most attractive feature of deterministic chaotic systems is he extremely unexpected and random-look nature of chaotic signals that may lead to novel applications. A novel image encryption algorithm based on compression and hyper chaotic map techniques is proposed. Firstly the image is decomposed into three subbands R, G, and B then each band is compressed using lossless technique. The generated chaotic sequences from the 3D chaotic system are employed to code the compressed results by employing the idea of chaotic shift encoding (CSK) modulation to encode the three bands to generate the encrypted image. The experiments show that the proposed method give good results in term of security, feasibility, and robustness.

The Iris localization plays a big role in the performance of an iris recognition system. This is due to the dependent of the next steps up on it, and the incorrect segmentation might lead to inexact normalization and improper feature extraction from less discriminatory parts (eyelids, eyelashes, pupil, etc.) so the execution of system will diminish. An effective method for locating the iris of the eye is suggested in this paper. At first a mixture of gamma transform and contrast enhancing mechanisms are used to guarantee a precise renovation of eye image to become an iris area easy to isolate. The next step is relayed on calculating the statistical image parameters (i.e., the mean and standard deviation) which are employed as a feature to detect outer iris boundary. The integro-differential operational technique is used with further pre-processing processes to detect the inner boundaries of iris. The noisy iris UBIRIS.v1 dataset was used in the experiment. Thee conducted results indicated that the proposed technique has a good performance, which is improved accuracy of iris localization step for noisy dataset.

The main challenges facing secure image sharing tasks are the increase of sharing volume and sharing-control flexibility. A new scheme based on DCT is developed to perform packet secret image sharing, the DCT is used to reduce the secret image size firstly, then it employs the (k, n) threshold sharing scheme to generate the shadow images. The main signal decomposition attribute of the transform is utilized to divide the secret image into uncorrelated shares. Expermintal results are given to illustrate the characteristic of this methods.

Background/Objectives: This paper presents a color image compression method to increase the compression ratio without affecting the original scene by noise or distortion. Methods/Analysis: In this paper an attempt to minimize data loss without highly affect the compression ratio by employing low lossy rate quad-tree compression technique to increase the correlation between pixels that will enhance DCT results and also compress the data before DCT phase, using Quantization and entropy encoders such as run length encoding and shift encoding will further compress the image. Finding: For conducted six different visual information images, the Compression Ratio (CR) results of the proposed method on average to be around 1:29 of the size of the original image, more compression ratio can be achieved by increasing the compression levels, this high compression ratio is considered a best ratio compared with the achieved Peak Signal to Noise Ratio (PSNR) of the decompressed-compressed image. Application/Improvements: This compression system can be used in Storing or Transforming Color Images due to its high compression ratio while the noise and distortion still as minimum as possible.

In this paper, a robust technique based on discrete wavelet transform, edge detection, and morphology operation for scene text detection is proposed. There are several stages in the proposed method. In the first stage, a single wavelet decomposition LH, HL and HH subbands are applied for detecting edges in original scene text image. The projection technique is applied in the second stage to preliminary detect text and non-text pixels. In third stage, 4-connected components are applied, and then area geometric feature is used as threshold to remove non-text region. At last stage, morphological operations are applied to connect isolated text components and to remove non-text regions. The proposed method is applied on a various images such as images of low contrast, complex background images and images of different fonts and size of text. The experimental results show that the proposed method can detect regions of the text perfectly.