Face recognition is one of the most commonly used biometric features in the identification of people. In this article, a novel facial image recognition architecture is proposed with a novel image descriptor which is called as fully center symmetric dual cross pattern (FCSDCP) The proposed architecture consists of preprocessing, feature extraction and classification phases. In the preprocessing phase, discrete wavelet transform (DWT) and Neutrosophy are used together to calculate coefficients of the face images. The proposed FCSDCP extracts features. LDA, QDA, SVM and KNN are utilized as classifiers. 4 datasets were chosen to obtain experiments and the results of the proposed method were compared to other state of art image descriptor based methods and the results clearly shows that the proposed method is a successful method for face classification.

In this paper, a novel discrete complex fuzzy transform (DCFT) and the proposed DCFT based facial image recognition method is presented. The presented DCFT consists of histogram extraction, peak points of histogram calculation and images construction. 3 real and 3 complex images are constructed using DCFT. Also, 3 angular images and 3 vector image are calculated using the real and complex images. To create real and complex images, polynomial and smith fuzzy sets are used in this paper. Briefly, 12 image are constructed using DCFT. In order to demonstrate effect of the proposed DCFT, face images data sets and local binary pattern (LBP) are used to create facial image recognition method. In this method, LBP is applied on the each DCFT image and 12 x 256 size of feature are extracted. Also, maximum pooling is applied on this feature set to obtain 256 size of feature. In the classification phase, support vector machine (SVM) and k nearest neighborhood (KNN) classifiers are used. The comparisons clearly demonstrate that the proposed DCFT is increased facial image recognition capability.

Fragile watermarking techniques have been widely used in the literature for tampered areas localization and image authentication. In this study, a novel quantum-dot cellular automata based fragile watermarking method for tampered area localization using chaotic piecewise map is proposed. Watermark generation, embedding, extraction and tampered area localization phases are consisted of the proposed quantum dot cellular automata and chaos based fragile watermarking method. In the watermark generation phase, quantum dot cellular automata and piecewise map which is a chaotic map are utilized. A block based method is utilized as authentication values embedding and extraction phases. To detect tampered areas, generated watermark and extracted watermark are compared. Also, block counters are used to tamper detection. In order to evaluate this method, capacity, imperceptibility and image authentication ability were utilized as performance metrics and the results of these metrics clearly illustrated that the presented method is suitable for image authentication and tamper detection.

Watermarking techniques are widely used for image authentication and copyright protection. Weaknesses of the “A novel CRT-based watermarking technique for authentication of multimedia contents,” [12] are analyzed in this study. 4 attacks are proposed to analysis of this method. These attacks are most significant bits, modulo number, tamper detection probability calculation and algorithm analysis attacks. The proposed attacks clearly show that the crt-based method is a data hiding method but this method is not used as image authentication method. The title of presented method in Ref. [12] include “authentication” but the authors of Ref. [12] evaluated their method in view of copyright protection. The fragile watermarking methods for image authentication should consist of watermark generation, watermark embedding, watermark extraction and tamper detection but Ref. [12] has no watermark generation, tamper detection and tampered area localization algorithms. The proposed attacks are demonstrated that Ref. [12] cannot be utilized as an image authentication method and Ref. [12] is not effectively coded.