A characterization of (regular) circular languages generated by monotone complete splicing systems

Circular splicing systems are a formal model of a generative mechanism of circular words, inspired by a recombinant behaviour of circular DNA. Some unanswered questions are related to the computational power of such systems, and finding a characterization of the class of circular languages generated by circular splicing systems is still an open problem. In this paper we solve this problem for monotone complete systems, which are finite circular splicing systems with rules of a simpler form. We show that a circular language L is generated by a monotone complete system if and only if the set Lin(L) of all words corresponding to L is a pure unitary language generated by a set closed under the conjugacy relation. The class of pure unitary languages was introduced by A. Ehrenfeucht, D. Haussler, G. Rozenberg in 1983, as a subclass of the class of context-free languages, together with a characterization of regular pure unitary languages by means of a decidable property. As a direct consequence, we characterize (regular) circular languages generated by monotone complete systems. We can also decide whether the language generated by a monotone complete system is regular. Finally, we point out that monotone complete systems have the same computational power as finite simple systems, an easy type of circular splicing system defined in the literature from the very beginning, when only one rule of a specific type is allowed. From our results on monotone complete systems, it follows that finite simple systems generate a class of languages containing non-regular languages, showing the incorrectness of a longstanding result on simple systems.     

Reliability assessment of principal point estimates for forensic applications

Although quite recent as a forensic research domain, computer vision analysis of scenes is likely to become more and more important in the near future, thanks to its robustness to image alterations at the signal level, such as image compression and filtering. However, the experimental assessment of vision-based forensic algorithms is a particularly critical task, since they cannot be tested on massive amounts of data, and their performance can heavily depend on user skill. In this paper we investigate on the accuracy and reliability of a vision-based, user-supervised method for the estimation of the camera principal point, to be used in cropping and splicing detection. Results of an extensive experimental evaluation show how the estimation accuracy depends on perspective conditions as well as on the selected image features. Such evidence led us to define a novel visual feature, referred to as Minimum Vanishing Angle, which can be used to assess the reliability of the method.     

Multi-scale noise estimation for image splicing forgery detection

Noise discrepancies in multiple scales are utilized as indicators for image splicing forgery detection in this paper. Specifically, the test image is initially segmented into superpixels of multiple scales. In each individual scale, noise level function, which reflects the relation between noise level and brightness of each segment, is computed. Those segments not constrained by the noise level function are regarded as suspicious regions. In the final step, pixels appears in suspicious regions of each scale, after necessary morphological processing, are marked as spliced region(s). The Optimal Parameter Combination Searching (OPCS) Algorithm is proposed to determine the optimal parameters during the process. Two datasets are created for training the optimal parameters and to evaluate the proposed scheme, respectively. The experimental results show that the proposed scheme is effective, especially for the multi-objects splicing. In addition, the proposed scheme is proven to be superior to the existing state-of-the-art method.     

On length-separating test tube systems

In this article we introduce a new variant of test tube systems based on splicing where the communication of the words among the test tubes is based on filtering by their lengths. The model, called length-separating test tube systems, is motivated by the gel electrophoresis laboratory technique. We prove that these constructs, even with restricted size parameters, simulate the Turing machines. We also discuss some natural restrictions and generalizations of the model, which may be used to find efficient ways to realize DNA transformations in the laboratory.     

Quaternion pseudo-Zernike moments combining both of RGB information and depth information for color image splicing detection

The quaternion representation (QR) used in current quaternion-based color image processing creates redundancy when representing a color image of three components by a quaternion matrix having four components. In this paper, both RGB and depth (RGB-D) information are considered to improve QR for efficiently representing RGB-D images. The improved QR fully utilizes the four-dimensional quaternion domain. Using this improved QR, firstly we define the new quaternion pseudo-Zernike moments (NQPZMs) and then propose an efficient computational algorithm for NQPZMs through the conventional pseudo-Zernike moments (PZMs). Finally, we propose an algorithm for color image splicing detection based on the NQPZMs and the quaternion back-propagation neural network (QBPNN). Experimental results on four public datasets (DVMM, CASIA v1.0 and v2.0, Wild Web) demonstrate that the proposed splicing detection algorithm can achieve almost 100% accuracy with the appropriate feature dimensionality and outperforms 14 existing algorithms. Moreover, the comparison of six color spaces (RGB, HSI, HSV, YCbCr, YUV, and YIQ) shows that the proposed algorithm using YCbCr color space has the overall best performance in splicing detection.     

面向DLP-3D打印的边缘灰度化拼接方案设计

针对传统数字光处理(DLP)-3D打印成品模型大小受到投影尺寸限制的问题,设计了一种基于拼接的掩模固化DLP-3D打印方案,对打印过程中拼接模型出现断裂的情况进行深入研究,根据材料的光化性质提出了一种边缘灰度化拼接策略,该方案将原始模型划分为多个子区域,设置重叠区域的灰度值与打印时间控制打印深度。通过实验测试了运用该方法的成型质量并进行实际模型打印,结果表明经过边缘灰度化策略的模型拼接质量明显提高。     

基于空间分解并行策略的演化算法研究

在分析已有的演化算法并行化实现策略的基础上，基于自强3000高性能计算机，设计实现了一种基于空间分解并行策略的演化算法（SP-PEA）。SP-PEA采用可分解／可拼接编码方式，使用了多种杂交和变异算子，获得了较好的收敛性能和可扩展性。在自强3000上的试验结果表明，SP-PEA在处理多维函数优化问题时与基于群体分组并行策略的演化算法相比有较好的收敛性能，能够以更快的速度收敛到最优解。     

超九卷接机组卷烟纸拼接第二直径检测的改进

超九卷接机组卷烟纸拼接直径在检测过程中容易出现偏差,造成卷烟纸浪费并会影响设备的有效作业率。通过改变检测点的方法,使卷烟纸拼接第二直径大小稳定且易于调整,降低了卷烟纸的消耗,保证了卷烟纸拼接的可靠性。