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Multi-scale Graph-matching Based Kernel for Character Recognition from Natural Scenes 基于多尺度图匹配的自然场景字符识别核
Q2 Computer Science
自动化学报
Pub Date : 2014-04-01 DOI: 10.1016/S1874-1029(14)60006-9
Cun-Zhao SHI , Chun-Heng WANG , Bai-Hua XIAO , Yang ZHANG , Song GAO

Recognizing characters extracted from natural scene images is quite challenging due to the high degree of intraclass variation. In this paper, we propose a multi-scale graph-matching based kernel for scene character recognition. In order to capture the inherently distinctive structures of characters, each image is represented by several graphs associated with multi-scale image grids. The similarity between two images is thus defined as the optimum energy by matching two graphs (images), which finds the best match for each node in the graph while also preserving the spatial consistency across adjacent nodes. The computed similarity is suitable to construct a kernel for support vector machine (SVM). Multiple kernels acquired by matching graphs with multi-scale grids are combined so that the final kernel is more robust. Experimental results on challenging Chars74k and ICDAR03-CH datasets show that the proposed method performs better than the state of the art methods.

自然场景图像中提取的特征由于类内变化很大，识别难度很大。本文提出了一种基于多尺度图匹配的场景字符识别核。为了捕获字符固有的独特结构，每个图像由多个与多尺度图像网格相关联的图表示。两幅图像之间的相似度被定义为通过匹配两幅图(图像)的最优能量，在保持相邻节点之间空间一致性的同时，找到图中每个节点的最佳匹配。计算得到的相似度适合于构造支持向量机的核。将多尺度网格图匹配得到的多个核结合起来，使最终核具有更强的鲁棒性。在挑战性Chars74k和ICDAR03-CH数据集上的实验结果表明，该方法优于现有方法。
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引用次数: 8
Data Driven Hierarchical Serial Scene Classification Framework 数据驱动的层次序列场景分类框架
Q2 Computer Science
自动化学报
Pub Date : 2014-04-01 DOI: 10.1016/S1874-1029(14)60008-2
Wen-Gang FENG

Scene classification is a complicated task, because it includes much content and it is difficult to capture its distribution. A novel hierarchical serial scene classification framework is presented in this paper. At first, we use hierarchical feature to present both the global scene and local patches containing specific objects. Hierarchy is presented by space pyramid match, and our own codebook is built by two different types of words. Secondly, we train the visual words by generative and discriminative methods respectively based on space pyramid match, which could obtain the local patch labels efficiently. Then, we use a neural network to simulate the human decision process, which leads to the final scene category from local labels. Experiments show that the hierarchical serial scene image representation and classification model obtains superior results with respect to accuracy.

场景分类是一项复杂的任务，因为它包含了很多内容，而且很难捕捉到它们的分布。提出了一种新的分层序列场景分类框架。首先，我们使用分层特征来表示包含特定对象的全局场景和局部补丁。层次结构是通过空间金字塔匹配来表示的，我们自己的密码本是由两种不同类型的单词组成的。其次，在空间金字塔匹配的基础上，分别采用生成和判别两种方法对视觉词进行训练，有效地获得局部贴片标签;然后，我们使用神经网络来模拟人类的决策过程，从而从局部标签中得出最终的场景类别。实验表明，该分级序列场景图像表示与分类模型在准确率方面取得了较好的效果。
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引用次数: 0
Fast Algorithm for Nonsubsampled Contourlet Transform 非下采样Contourlet变换快速算法
Q2 Computer Science
自动化学报
Pub Date : 2014-04-01 DOI: 10.1016/S1874-1029(14)60007-0
Chun-Man YAN , Bao-Long GUO , Meng YI

The multiscale geometric analysis (MGA) has been recognized as an effective strategy for image processing. As one of the discrete tools of MGA, the nonsubsampled contourlet transform (NSCT) has been widely used for image denoising, image fusion, image enhancement, feature extraction and so on. However, the processing performance is limited due to its high redundancy, and leading to an intensive computational efficiency. Therefore, its fast algorithm is desired in practice. In this paper, we adopt an optimized directional filter bank (DFB) and embed it into the NSCT to significantly accelerate the computational speed while keeping slight loss of the reconstructed performance. Experimental results show that the reconstructed image quality can satisfy the human visual system. Moreover, the improved NSCT has a speed about several times than that of the traditional one. Experimental results on image denoising also validate the feasibility and efficiency of the proposed method.

多尺度几何分析(MGA)是一种有效的图像处理方法。非下采样contourlet变换(NSCT)作为MGA的离散化工具之一，在图像去噪、图像融合、图像增强、特征提取等方面得到了广泛的应用。然而，由于其高冗余性，限制了处理性能，导致了大量的计算效率。因此，在实际应用中需要快速的算法。在本文中，我们采用了一种优化的方向滤波器组(DFB)并将其嵌入到NSCT中，在保持重构性能轻微损失的同时显著加快了计算速度。实验结果表明，重构后的图像质量能够满足人眼视觉系统的要求。此外，改进的NSCT的速度是传统NSCT的几倍左右。图像去噪的实验结果也验证了该方法的可行性和有效性。
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引用次数: 14
Control of Genetic Regulatory Networks: Opportunities and Challenges: Control of Genetic Regulatory Networks: Opportunities and Challenges 遗传调控网络的控制:机遇与挑战:遗传调控网络的控制:机遇与挑战
Q2 Computer Science
自动化学报
Pub Date : 2014-03-28 DOI: 10.3724/SP.J.1004.2013.01969
Pei-ju Wang, Jinxing Lv
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引用次数: 18
Research on Differential Constraints-based Planning Algorithm for Autonomous-driving Vehicles: Research on Differential Constraints-based Planning Algorithm for Autonomous-driving Vehicles 基于差分约束的自动驾驶车辆规划算法研究基于差分约束的自动驾驶车辆规划算法研究
Q2 Computer Science
自动化学报
Pub Date : 2014-03-28 DOI: 10.3724/SP.J.1004.2013.02012
Y. Jiang, Jian-wei Gong, Guang-ming Xiong, Huiyan Chen
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引用次数: 10
Alternating Direction Method for Salt-and-pepper Denoising: Alternating Direction Method for Salt-and-pepper Denoising 椒盐去噪的交替方向法:椒盐去噪的交替方向法
Q2 Computer Science
自动化学报
Pub Date : 2014-03-28 DOI: 10.3724/SP.J.1004.2013.02071
Q. Xue, Chengyi Yang, Huaxiang Wang
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引用次数: 1
Comparison of Two Methods to Implement Backward Swimming for a Carangiform Robotic Fish: Comparison of Two Methods to Implement Backward Swimming for a Carangiform Robotic Fish 囊状机器鱼向后游泳的两种实现方法的比较:囊状机器鱼向后游泳的两种实现方法的比较
Q2 Computer Science
自动化学报
Pub Date : 2014-03-28 DOI: 10.3724/SP.J.1004.2013.02032
Wu Zheng-xing, Yu Junzhi, Min Tan
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引用次数: 2
Rescheduling with Release Time to Minimize Sum of Waiting Time Considering Waiting Constraint of Original Loads 考虑原负载等待约束的带释放时间的最小等待时间重调度
Q2 Computer Science
自动化学报
Pub Date : 2014-03-28 DOI: 10.3724/SP.J.1004.2013.02100
Yan-Dong Guo, Wang Qing, Huang Min
In this paper, we consider the rescheduling problem to minimize the sum of waiting times of rework jobs and the original loads with release time on a single machine, and the waiting time of each original load is constrained by a value. The problem of rescheduling for reworks on a single machine (RRSM) is formulated and proved to be NP-hard. A dynamic insert heuristic (DIH) algorithm of polynomial-time is designed and proved with three properties. With respect to two special cases of the identical processing time of rework jobs or the machine without idle times in the original schedule, the DIH algorithm can obtain an optimal solution. A discrimination condition is proved for the optimal solution and efiectiveness of the DIH algorithm is explained by cases with regard to general RRSM problems.
本文考虑重调度问题，以最小化单机上的返工作业与具有释放时间的原始负载的等待时间总和，并且每个原始负载的等待时间都有一个值约束。提出了单机返工的重调度问题，并证明了该问题具有np困难。设计了一种多项式时间的动态插入启发式(DIH)算法，并证明了它具有三个性质。对于返工作业加工时间相同或原计划中机器无空闲时间的两种特殊情况，DIH算法可以得到最优解。对于一般的RRSM问题，证明了最优解的判别条件，并通过实例说明了DIH算法的有效性。
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引用次数: 9
On the Relationship between the Synchronous State and the Solution of an Isolated Node in a Complex Network: On the Relationship between the Synchronous State and the Solution of an Isolated Node in a Complex Network 复杂网络中孤立节点的同步状态与解的关系——复杂网络中孤立节点的同步状态与解的关系
Q2 Computer Science
自动化学报
Pub Date : 2014-03-28 DOI: 10.3724/SP.J.1004.2013.02111
Juan Chen, Jun-an Lu, Jin Zhou
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引用次数: 4
Research Advances on Structured Compressive Sensing: Research Advances on Structured Compressive Sensing 结构化压缩感知研究进展:结构化压缩感知研究进展
Q2 Computer Science
自动化学报
Pub Date : 2014-03-28 DOI: 10.3724/SP.J.1004.2013.01980
Fang Liu, Jiao Wu, Shuyuan Yang, L. Jiao
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引用次数: 5
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