A hybrid domain image encryption algorithm is developed by integrating with improved Henon map, integer wavelet transform (IWT), bit-plane decomposition, and deoxyribonucleic acid (DNA) sequence operations. First, we improve the classical two-dimensional Henon map. The improved Henon map is called 2D-ICHM, and its chaotic performance is analyzed. Compared with some existing chaotic maps, 2D-ICHM has larger parameter space, continuous chaotic range, and more complex dynamic behavior. Second, an image encryption structure based on diffusion–scrambling–diffusion and spatial domain–frequency domain–spatial domain is proposed, which we call the double sandwich structure. In the encryption process, the diffusion and scrambling operations are performed in the spatial and frequency domains, respectively. In addition, initial values and system parameters of the 2D-ICHM are obtained by the secure hash algorithm-512 (SHA-512) hash value of the plain image and the given parameters. Consequently, the proposed algorithm is highly sensitive to plain images. Finally, simulation experiments and security analysis show that the proposed algorithm has a high level of security and strong robustness to various cryptanalytic attacks.

This paper constructs a two-dimensional Logistic-Sine-Henon map (2D-LSHM) for image encryption. By comparing with some existing chaotic systems, the 2D-LSHM has better chaotic performance and is more suitable for image encryption scenarios. Using the 2D-LSHM, we propose a double image adaptive encryption algorithm consisting of bit-level combinatorial permutation and four-directional adaptive diffusion called LSHM-DIAEA. Differently from traditional image encryption algorithms, the proposed LSHM-DIAEA can encrypt a color image and a grayscale image at the same time so that the information from each other can be fused and affected by each other, which makes the encryption process more secure and efficient. In addition, to enhance plaintext sensitivity, we introduce the secure hash algorithm-512 (SHA-512) and the Histogram of Oriented Gradient (HOG) feature extraction algorithm into the LSHM-DIAEA. Simulation and security analysis results illustrate that the LSHM-DIAEA provides a high security level to resist various cryptanalytic attacks and a high execution efficiency.

This paper introduces the design of the autonomous tracing intelligent vehicle. The software and hardware design method which realizes the autonomous tracing using the infrared reflective photoelectric sensors as the path recognition module is researched. The system employs Freescale HCS series 16 bit single-chip microcomputer MC9SDG128 as its main controller and an array of photoelectric sensors for recognizing the path information. Single-chip Microcomputer energizes the servo to steer and control the speed of the DC electric motor according to the analysis of the path and speed information that from sensors. Consequently this intelligent vehicle can track the black-guideline automatically and move forward following the line quickly and smoothly. The autonomous tracing principle of photoelectric sensor is presented. The effect of sensors overall arrangement and space on the autonomous trace is discussed.