Applied Mechanics and Materials Vols. 719-720

Abstract: In this paper, we propose a real time method to detect vehicles on road by using a vehicle mounted monocular camera. Based on lane detection design, low time cost and high accuracy vehicle detecting and tracking algorithm is achieved. Robust and fast lane detection has been achieved using Hough transform in combination with a line merging method. The lane data are used for effective vehicle hypothesis generation. A subsequent validation, based on the area ratio of hypothesis vehicle, is used to eliminate false positives. Further, a data fusion mechanism is proposed to incorporate temporal information for stably updating vehicle detection results over time. Experimental results show that, without specific hardware and software optimizations, our method is able to detect vehicles on road with low false alarm rate at real time speeds of 30 frames per second.

Abstract: The proliferation of digitized media due to rapid growth of network multimedia systems has created an urgent need for information security due to the ever increasing unauthorized manipulation and reproduction of original digital data. In this paper an approach based on Merkle-Hellman, ElGamal and Genetic algorithms is proposed for data encryption and decryption. The strength of the cipher is increased further by using genetic algorithm. Experimental results show that the proposed approach can be implemented on images of any size which retain the quality of the image while retrieving the original image. This aspect helps in providing the reduction in block size without compromise in the quality of the image and security as well.

Abstract: As known, there always exist severely degradation problems in digital radiography. How we can extract necessary textures from degraded radiographic images is the post-processing key. Local binary pattern (LBP) is a well-known method, which is widely used in fast image texture extraction. However, for noisy images, LBP can’t work well due to its sensitivity to details. On the other hand, as one of the important shock filters developed in recent years, complex shock filter possesses excellent capabilities in textural image processing. Here, by combining complex shock filter with LBP, a novel fast and efficient method, C-LBP is presented for texture extraction of degraded radiographic images. Experimental results show that comparing with traditional LBP, C-LBP not only distinguishes between noise and details in radiographic images, but also extracts image textures efficiently and rapidly, which plays an important role in developing nondestructive detection technique by low-dose ray radiography.

Abstract: The local region term and global region term are combined for image segmentation. Intensity information in local regions is utilized by adding a kernel function in the data fitting term. Experiments have been done on different images to compare the effectiveness of our methods with that of the classic CV model, Li’s Local Binary Fitting (LBF) model. Experiment results show that the new model maintain more satisfactory segmentation results.

Abstract: Clustering analysis continually consider as a hot field in Data Mining. For different types data sets and application purposes, the relevant researchers concern on various aspect, such as the adaptability to fit density and shape, noise detection, outliers identification, cluster number determination, accuracy and optimization. Lots of related works focus on the Shared Nearest Neighbor measure method, due to its best and wide adaptability to deal with complex distribution data set. Based on Shared Nearest Neighbor, an improved algorithm is proposed in this paper, it mainly target on the problems solution of natural distribute density, arbitrary shape and cluster number determination. The new algorithm start with random selected seed, follow the direction of its nearest neighbors, search and find its neighbors which have the greatest similar features, form the local maximum cluster, dynamically adjust the data objects’ affiliation to realize the local optimization at the same time, and then end the clustering procedure until identify all the data objects. Experiments verify the new algorithm has the advanced ability to fit the problems such as different density, shape, noise, cluster number and so on, and can realize fast optimization searching.

Abstract: A Hash authentication algorithm of speech perception based on MDCT coefficients was proposed to solve the problems of large amount of computation and bad real-time capability when using traditional authentication algorithm in compressed domain speech. Firstly, the algorithm extracts MDCT coefficients by partly decompressing speech sound in MP3 format. Then MDCT coefficients of each frame of speech are processed by Mel filter in the compressed domain, forming the 15-dimensional MFCC coefficient vector. Finally the perceptual Hash string is generated by Hash structure. The perceptual Hash string can perceive the content of voice authentication. Experimental results show that the algorithm keeping on content presents the strong robustness and good real-time capability.

Abstract: For solving the problem which the performance of detection was reduced in the low signal to noise ratio (SNR) using Wigner-Ville Hough transform (WHT), the method of XWVD adaptive mean Ridgelet transform filtering (XWVD-M-FRIT) was proposed. In this method, due to the power distribution of signal is different from noise or reverberation in time-frequency domain, so designed adaptive axial mean filter, then using Ridgelet transform filtering to restrain noise or reverberation. At last, it is to detect the signal using Hough transform. The results of real and simulation experiments showed, compared with WHT, in the low SNR the new method is feasible to restrain noise or reverberation in time-frequency domain for improving the performance of signal detection. furthermore, the performance of varying implement of adaptive mean and Ridgelet transform filtering were compared.

Abstract: Intra prediction is a key step in H.264/AVC to improve the coding performance with the idea that removing the directional redundancy among neighboring blocks. In order to cover more directional information existed in the image frames, there are usually many prediction modes can be selected in the state-of-the-art coding frameworks, but more bits are also needed to encode the prediction mode index information, then how to achieve the maximum overall bit-rate reduction became a problem. In this paper, 16 kinds of prediction modes are adopted by considering the direction information for 8x8 image blocks. Through calculating the bit-rate both for the mode index and residual image under different number of prediction modes, we obtain the most suitable prediction mode number relatively from the graphs. Experimental results show that, with the increase of prediction mode number, the residual information decreases obviously, and the sum of residual information and prediction mode index information also decreases but levels off after reaching a certain mode number, even has an obviously rising trend.

Abstract: The optimization of the camera’s intrinsic and extrinsic parameters is a key step after obtaining the initialized parameters’ state by considering the homography between the board space plane and the image plane in Zhengyou Zhang method. In this paper, we proposed a camera calibration optimization algorithm by adopting genetic algorithm and the simulated annealing algorithm. The experiment results demonstrate that our algorithm can improve the precision of the camera calibration to a certain extent.

Abstract: This paper is focused on camera calibration, image matching, both of which are the key issues in three-dimensional (3D) reconstruction. In terms of camera calibration firstly, we adopt the method based on the method proposed by Zhengyou Zhang. In addition to this, it is selective for us to deal with tangential distortion. In respect of image matching, we use the SIFT algorithm, which is invariant to image translation, scaling, rotation, and partially invariant to illumination changes and to affine or 3D projections. It performs well in the follow-up matching the corresponding points. Lastly, we perform 3D reconstruction of the surface of the target object. A Graphical User Interface is designed to help us to realize the key function of binocular stereo vision, with better visualization. Apparently, the entire GUI brings convenience to the follow-up work.