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Soft Computing: Theories and Applications 1st ed. 2018

丛书名： Advances in Intelligent systems and Computing

2018年

作者： Millie Pant Kanad Ray Tarun K. Sharma Sanyog Rawat Anirban Bandyopadhyay

ISBN: (数字)9789811056871

ISBN: (纸本)9789811056864

This book focuses on soft computing and its applications to solve real-life problems occurring in different domains ranging from medical and health care, supply chain management and image processing to cryptanalysis. It presents the proceedings of International Conference on Soft Computing: Theories and Applications (SoCTA 2016), offering significant insights into soft computing for teachers and researchers and inspiring more and more researchers to work in the field of soft computing. The term soft computing represents an umbrella term for computational techniques like fuzzy logic, neural networks, and nature inspired algorithms. In the past few decades, there has been an exponential rise in the application of soft computing techniques for solving complex and intricate problems arising in different spheres of life. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. SoCTA is the first international conference being organized at Amity University Rajasthan (AUR), Jaipur. The objective of SoCTA 2016 is to provide a common platform to researchers, academicians, scientists, and industrialists working in the area of soft computing to share and exchange their views and ideas on the theory and application of soft computing techniques in multi-disciplinary areas. The aim of the conference is to bring together young and experienced researchers, academicians, scientists, and industrialists for the exchange of knowledge. SoCTA especially encourages the young researchers at the beginning of their career to participate in this conference and present their work on this platform.

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Effect of Temporal and Spatial Noise on the Performance of Hardware Oriented Background Extraction algorithms 15

Effect of Temporal and Spatial Noise on the Performance of H...

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15th IEEE International New Circuits and systems Conference (NEWCAS)

作者： Garcia-Lesta, D. Brea, V. M. Lopez, P. Cabello, D. Univ Santiago de Compostela Ctr Singular Invest Tecnoloxias Informac CiTIUS Santiago De Compostela Spain

ISBN: (纸本)9781509049912

Background extraction is a fundamental task present in most computer vision applications such as video surveillance, optical motion capture or multimedia applications. In this paper we explore a particular foreground segmentation method based on the well-known Pixel-based Adaptive Segmenter (PBAS) algorithm, proposing modifications that will ease the hardware implementation. Also, the figures of merit of a focalplane approach for foreground segmentation are studied through the impact of typical temporal and spatial noise sources present in the processing elements of smart image sensors such as leakage currents from analog memories or fixed pattern noise (FPN) from mismatch.

关键词： Smart image Sensors Focal-Plane Procesing Background subtraction PBAS hardware implementation

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A Novel Algorithm for Laser Spot Detection Based on Quaternion Discrete Cosine Transform

A Novel Algorithm for Laser Spot Detection Based on Quaterni...

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International Conference on Intelligent and Interactive systems and Applications (IISA)

作者： Miao, Xiaodong Shi, Xiang Xu, Zhixing Wang, Aiqing Wang, Wei Kangni Mech & Elect Co Ltd Nanjing 210009 Jiangsu Peoples R China Nanjing Univ Technol Sch Mech & Power Engn Nanjing 211800 Jiangsu Peoples R China

ISBN: (纸本)9783319495682;9783319495675

Laser spot detection is an important problem in optical measurement. The precision and speed of the detection algorithm influence the optical measurement system directly. The traditional algorithms such as Hough Transform and Gravity model are unsatisfactory in complex conditions. The laser spot detection algorithm referred in this paper is based on the quaternion discrete cosine transform and moment and a method is adopted to approximate the edge of the laser spot. Not only the center and edge can be detected simultaneously but also the robustness of noise is better than others. The algorithm is suitable for the real-time optical measurement.

关键词： Laser spot image processing Quaternion discrete cosine transform

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Automatic Color Detection of Grape Based on Vision Computing Method

Automatic Color Detection of Grape Based on Vision Computing...

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International Conference on Intelligent and Interactive systems and Applications (IISA)

作者： Wang, Yue Luo, Jun Wang, Qiaohua Zhai, Ruifang Peng, Hui Wu, Liang Zong, Yuhua Huazhong Agr Univ Coll Informat Wuhan 430070 Peoples R China Huazhong Agr Univ Coll Engn Wuhan 430070 Peoples R China North Xinjiang Fruit & Vegetable Ind Dev Co Ltd Bole 833400 Peoples R China

ISBN: (纸本)9783319495682;9783319495675

The vision characteristics-based on image detection techniques are functional method, which are appropriate for many industrial and agricultural applications. The color detection method is such a technique for non-destructive grading of the grape after the harvest process, which have been widely used in a variety of fruits' quality inspection and grading aspects based on vision computing method. However, the shapes of the entire bunch of grapes are obviously different with each other, which will influence the accuracy of non-destructive detection. This work develops a method for image detection and color grading of red and black grape samples, which uses vision computing technology to extract the effective color features of red and black grape samples, the experimental results show that the effective region extraction and color detection algorithms are feasible for color detection of grape.

关键词： Grape image processing Color detection Vision computing

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Use of OWA Operators for Feature Aggregation in image Classification

Use of OWA Operators for Feature Aggregation in Image Classi...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Pagola, Miguel Forcen, Juan I. Barrenechea, Edurne Lopez-Molina, Carlos Bustince, Humberto Univ Publ Navarra Inst Smart Cities Pamplona 31006 Spain

ISBN: (纸本)9781509060344

Feature aggregation is a crucial step in many methods of image classification, like the Bag-of-Words (BoW) model or the Convolutional Neural Networks (CNN). In this aggregation step, usually known as spatial pooling, the descriptors of neighbouring elements within a region of the image are combined into a local or a global feature vector. The combined vector must contain relevant information, while removing irrelevant and confusing details. Maximum and average are the most common aggregation functions used in the pooling step. To improve the aggregation of relevant information without degrading their discriminative power for classification in this work we propose the use of Ordered Weighted operators. We provide an extensive evaluation that shows that the final result of the classification using OWA aggregation is always better than average pooling and better than maximum pooling when dealing with small dictionary sizes.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Generalizing an Interval-Valued image Magnification Algorithm Using Homogeneity Measures and Interval Fusion Functions 17

Generalizing an Interval-Valued Image Magnification Algorith...

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Joint 17th World Congress of International-Fuzzy-systems-Association / 9th International Conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Paternain, Daniel Jurio, Aranzazu Pagola, Miguel Barrenechea, Edurne Bustince, Humberto Univ Publ Navarra Dept Automat & Comp Pamplona 31006 Spain Univ Publ Navarra Inst Smart Cities Pamplona 31006 Spain

ISBN: (纸本)9781509049172

In this work we study and generalize an image magnification algorithm based on the use of interval-valued fuzzy sets. The first proposed generalization incorporates an homogeneity measure that allows to model the length of the intervals generated by the algorithm. The second one makes use of several homogeneity measures and, by means of a fusion function, it combines the intervals generated by each individual homogeneity measure. The results show that our generalization outperforms the original algorithm when an appropriate homogeneity measure is used. Moreover, experiments have demonstrated that the second generalization, based on interval fusion functions, avoids low quality results due to bad homogeneity measures.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Single-image Blind Deconvolution Using Gradient Saliency Map 36

Single-Image Blind Deconvolution Using Gradient Saliency Map

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第36届中国控制会议

作者： Xiaoguang Di Lei Yin Control and Simulation Center Harbin Institute of Technology

ISBN: (纸本)9781538629185

Single-image blind deconvolution is one of the most challenging fields in image processing which restores a sharp image from its blurred *** blind deconvolution algorithms have made significant ***,the restoration of blurred images with little scale edges and periodic textures is still a hard *** solve this problem,this paper proposes a new normalized sparse regularization blind deconvolution algorithm,which uses a gradient saliency map to prohibit the image small structures on image blurry kernel ***,salient detection is performed to select the important area which conforms with the human vision system and generates a binary mask to screen out useful ***,the normalized sparse regularization blind deconvolution method is applied to obtain accurate blur kernel and recover the sharp ***,the experiment results show that the algorithm can effectively deblur the degraded image on different scenarios.

关键词： blind deconvolution sparse regularization salient detection gradient map

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基于模糊综合评判的在线图像分割

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有色金属（矿山部分） 2019年第2期71卷 99-107页

作者：林坚普王卫星严群郭太良姚剑敏林志贤白莉娜福州大学物理与信息工程学院福州350108 瑞典皇家工学院斯德哥尔摩se10044

为使矿岩块度在线检测能精确和快速地进行,提出了一种自适应阈值分割算法:首先选取全局自动阈值分割算法粗分割图像,然后针对粗分割效果较差的目标区域,重复利用阈值分割算法直到无区域可分离。在重复分割前,利用模糊综合评判方法对每... 详细信息

为使矿岩块度在线检测能精确和快速地进行,提出了一种自适应阈值分割算法:首先选取全局自动阈值分割算法粗分割图像,然后针对粗分割效果较差的目标区域,重复利用阈值分割算法直到无区域可分离。在重复分割前,利用模糊综合评判方法对每一个目标物体的参数(尺寸,形状及梯度等)进行综合评价,若该目标为非正常块度,对其进行重复分割。通过对一次矿山爆破的300多幅矿岩块度图像进行测试表明:在线图像分割算法与新近的聚类分析及图论最小割算法相比,不仅简单而且具有较好的分割效果,在保证在线处理速度的要求下,分割准确率达95%以上,可有效地扩展应用在其它颗粒在线检测系统中。

关键词：矿岩块度图像分割模糊综合评判自适应阈值

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A New Method to Detect Moving Targets

A New Method to Detect Moving Targets

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2018 3rd International Conference on Education, Management and systems Engineering(EMSE 2018)

作者： Yang-ming HE Ya-fen WU School of Computer Jiangxi University of Traditional Chinese Medicine Office of Academic Research Jiangxi University of Traditional Chinese Medicine

In the moving target detection, there are a lot of methods. But the effects of those algorithms are limited, especially in complex environment. This paper putts forward a new method to detect moving targets, which uses virtual binocular disparity. It is called virtual because the environment uses one camera but the theory is about two cameras. Virtual binocular disparity algorithm regards moving targets as static targets under two cameras. It uses two neighboring images, the current frame image and the next frame image. The algorithm looks the two images as two static images under two cameras, then uses stereo match theory to calculate the disparity of the neighboring images. Because the background of the two images is the same, the disparity of their background is about zero. And the disparity of moving targets is positive or negative. The sign of disparity means the direction of targets moving. So we can use the sign of disparity to distinguish the targets moving in different directions. The direction detected out will be helpful for subsequent work, for example, targets tracking and counting etc. This algorithm fully uses the continuity property of moving targets, so it can have good effect. In the end of the paper, experiments are used to prove the algorithm.

关键词： Virtual binocular disparity Stereo match Moving targets image processing

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Flexible image processing in Embedded systems using Multi-agents systems

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IFAC-PapersOnLine 2016年第25期49卷 164-169页

作者： Inguère, Tifaine Carlier, Florent Renault, Valérie CREN University of Maine Le Mans France STMicroelectronics Le Mans France

Efficient image processing can lead to complex algorithms. In Embedded context resources are limited and the approach of linear algorithm does not allow to decrease complexity regarding the variations of these resources availability. Agents are autonomous entities brought together into systems. They interact between them and with their environment to perform tasks. Their interactions allow them to share knowledge and capacities in order to adapt themselves to a changing context. In this paper we propose to use Multi-agents systems algorithms to perform flexible image processing in an Embedded context. We will introduce our hardware context and the architecture choices made to adapt Multi-agents systems to the Embedded field. We will then present an experiment focusing on pixel interpolation process to study the flexibility of our solution. © 2016

关键词： Embedded systems Autonomous agents image processing Lead compounds Multi agent systems Resource allocation Autonomous entities Complex algorithms Decrease complexity Embedded fields Linear algorithms Management systems Multi agents systems Share knowledge

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