Encryption security and encryption speed are two important aspects of image encryption algorithms. Due to their increasingly large size, video images present a great challenge to currently available cryptographic algorithms; the processes of encryption and decryption of images are so computationally intensive that they introduce delays beyond acceptable real-time application limits. [1] In this paper we introduce a new algorithm that uses Dynamic Total Shuffling as both encryption keys and the control stream to verify which key will be used for each block.The goal is to provide a highly secure encryption algorithm with a wide space for encryption speed.
Encryption security and encryption speed are two important aspects of image encryption algorithms. Due to their increasingly large size, video images present a great challenge to currently available cryptographic algorithms; the processes of encryption and decryption of images are so computationally intensive that they introduce delays beyond acceptable real-time application limits. [1] In this paper we introduce a new algorithm that uses dynamic square matrices as both encryption keys and the control stream to verify which key will be used for each block. The study case showed in this paper works on GF(7) and for encryption key sizes varying from 3X3 to 12X12 The goal is to provide a highly secure encryption algorithm with a wide space for encryption speed.
Tracking moving objects from moving platform in videos sequence is a challenging task .object movement and platform movement are sources of variations in scene. Mean Shift Algorithm (MSA) is the common tracking algorithm due simple and efficient procedure. Correct Background Weight Histogram(CBWH)decrease background effect in target representation module. The main drawbacks in MSA is the ineffective model representation to handle illumination variation and occultation problems. MSA failed to track objects in video containing wide ranges of variations and background motion. In this paper motion information is exploited from edge flow by gradient differential. Histogram for edge flow combined with color histogram called Motion Flow Histograms (MFH).MFH used to represent tracking target between two successive frames. New module target representation reduces the false tracker rate without evident increasing time compare to the classical tracking MSA and CBWH.
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