In the photovoltaic system, the performance, efficiency, and generated power of the PV system are affected by changes in the environment, disturbances, and parameter variations, and this leads to a deviation from the operating maximum power point (MPP) of the PV system. Therefore, the main aim of this paper is to ensure the PV system operates at the maximum power point under the influence of exogenous disturbances and uncertainties, i.e., no matter how the irradiation, temperature, and load of the PV system change, by proposing a maximum power point tracking for the photovoltaic system (PV) based on the active disturbance rejection control (ADRC) paradigm. The proposed method provides better performance with excellent tracking for the MPP by controlling the duty cycle of the DC–DC buck converter. Moreover, comparison simulations have been performed between the proposed method and the linear ADRC (LADRC), conventional ADRC, and the improved ADRC (IADRC) to investigate the effectiveness of the proposed method. Finally, the simulation results validated the accuracy of the proposed method in tracking the desired value and disturbance/uncertainty attenuation with excellent response and minimum output performance index (OPI).

Recently, researchers focused on face image manipulation detection and localization techniques because of their importance in image security applications. The previous research has not highlighted the recovery of the face region after manipulation detection. This paper presents a new face region recovery algorithm (FRRA) to be included in the face image manipulation detection algorithms (FIMD). The proposed FRRA consists of two main algorithms: face data generation algorithm and face region restoration algorithm. Both algorithms start by detecting the face region using Multi-task Cascaded Neural Network followed by a face window selection process. In the face data generation algorithm, the recovery information is generated from the shirked face window using bicubic interpolation technique. In the face region restoration algorithm, the face region zoomed using bicubic interpolation technique. The proposed FRRA has been tested and compared with previous recovery methods for different color face images, and the results proved that the FRRA could recover the face region with better visual quality at the same data length compared to previous methods. The main contributions of this research are a) the suggestion of including a face region recovery algorithm to FIMD, b) the study of previous recovery data generation algorithms for color face images, and c) introducing a new algorithm for generating the recovery data based on bicubic interpolation. In the future, the proposed algorithm can be included in the recent FIMD algorithms to recover the face region, which can be very useful in practical applications, especially those used in data forensics systems.

Nowadays, image manipulation algorithms are increasingly being used even by people who do not have any deep knowledge of technology, and one can easily find an application to manipulate face image for various purposes. After the development of image processing algorithms, the research community highlighted the need to develop a technology that detects image manipulation, but it did not highlight the recovery of the facial region after manipulation localization, which would be very useful in practical applications. In this paper, a new face image modification detection and recovery scheme based on image watermarking and bicubic interpolation algorithm is presented. Several experiments were conducted to evaluate the performance of the proposed scheme, which proved its effectiveness in generating high-quality watermarked images, detecting different types of manipulation, localizing the manipulated blocks in the face region, and restoring the face region with good visual quality. A comparison with the latest detection techniques demonstrates the superiority of the proposed scheme.

Iris-based security systems are highly recommended because of their security and ease of use. Different watermarking techniques have been presented to provide security while exchanging or storing iris images. The previous iris image watermarking techniques have successfully reached their aims, however, they suffer from some limitations such as the distortions that are presented in the iris region because of the watermark embedding process, the limited embedding capacity, and the lack of robustness against unintentional attacks. On the other hand, nowadays, the biometric-based security systems have directed their interest towards multi-biometric techniques in order to improve the performance of the individual’s recognition process. This paper presents a new multi-biometric watermarking (MBW) scheme in which the features of the fingerprint image and some personal information are embedded in the iris image. To avoid the abovementioned limitations, the proposed scheme presents an interactive segmentation algorithm (ISA) and a Slantlet transform based watermark embedding method. The proposed ISA prevents any distortion in the iris region which is a beneficial feature for the iris image recognition process. The experimental results proved the efficiency of the proposed ISA in comparison with the Hough transform based methods in terms of accuracy, embedding capacity, and execution time. The proposed MBW scheme performs better in comparison with the state-of-the-art methods in terms of the intactness of the iris region, the robustness against unintentional attacks, and the watermark embedding capacity.