Journal of Intelligent & Fuzzy Systems - Volume 39, issue 4

Authors: Jin, Zhi | Ge, Dong-Yuan

Article Type: Research Article

Abstract: Intelligent vehicle technology has become a research hot issue in recent ten years, the reason is that intelligent vehicles can not only be used as a flexible weapon platform in the military. And in life, it is also a system that provides convenience and security for people. For example, driverless cars and advanced driver assistance systems (ADAS). Information processing is the key to the degree of intelligence, and the detection and recognition of traffic safety information based on monocular vision is the core of information processing, it’s also the bottleneck problem. Because of the complexity and diversity of the environment …have brought great challenges to this problem. In this paper, the existing lane detection methods in structured and semi-structured roads do not specifically consider the problem of weak line detection, two models are proposed. Fuzzy LDA enhancement model is used to enhance the contrast of lane area, another brightness contrast saliency model can be used for robust Lane extraction. Then, two models are applied to lane detection, a two-stage lane detection method is proposed and a blind area vehicle detection method is designed. Firstly, the vehicle area is roughly extracted based on road gray statistics, and then the typical vehicle features are screened finely. Finally, the extracted features and SVM classifiers are used to confirm the candidate regions. Experiments show that: The proposed method can detect the vehicle in the blind area very well and is insensitive to the shape distortion and size change of the vehicle. Show more

Keywords: Intelligent vehicle, monocular vision, driving safety information detection, vehicle characteristics

DOI: 10.3233/JIFS-179987

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5017-5026, 2020

Authors: Lu, You | Fu, Qiming | Xi, Xuefeng | Chen, Zhenping

Article Type: Research Article

Abstract: Data outsourcing has gradually become a mainstream solution, but once data is outsourced, data owners will without the control of the data hardware, there is a possibility that the integrity of the data will be destroyed objectively. Many current studies have achieved low network overhead cloud data set verification by designing algorithmic structures (e.g., hashing, Merkel verification trees); however, cloud service providers may not recognize the incompleteness of cloud data to avoid liability or business factors fact. There is a need to build a secure, reliable, non-tamperable, and non-forgeable verification system for accountability. Blockchain is a chain-like data structure constructed …by using data signatures, timestamps, hash functions, and proof-of-work mechanisms. Using blockchain technology to build an integrity verification system can achieve fault accountability. Blockchain is a chain-like data structure constructed by using data signatures, timestamps, hash functions, and proof-of-work mechanisms. Using blockchain technology to build an integrity verification system can achieve fault accountability. This paper uses the Hadoop framework to implement data collection and storage of the HBase system based on big data architecture. In summary, based on the research of blockchain cloud data collection and storage technology, based on the existing big data storage middleware, a large flow, high concurrency and high availability data collection and processing system has been realized. Show more

Keywords: Blockchain, data acquisition, data processing

DOI: 10.3233/JIFS-179988

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5027-5036, 2020

Authors: Wei, Peng-Cheng | He, Fangcheng | Li, Jing

Article Type: Research Article

Abstract: Nowadays, moving object detection in sequence images has become a hot topic in computer vision research, and has a very wide range of practical applications in many fields of military and daily life. In this paper, fast detection of moving objects in complex background is studied, and fast detection methods for moving objects in static and dynamic scenes are proposed respectively. Firstly, based on image preprocessing, aiming at the difficulty of feature extraction of moving targets in low illumination at night, Gamma change is used to process. Secondly, for the fast detection of moving objects in static scenes, this paper …designs a detection method combining background difference and edge frame difference. Finally, aiming at the fast detection of moving objects in dynamic scenes, a feature matching detection method based on the SIFT algorithm is designed in this paper. Simulation experiments show that the method designed in this paper has good detection performance. Show more

Keywords: Keywords: Sequence image, fast detection of moving objects, Gamma change, SIFT algorithm

DOI: 10.3233/JIFS-179989

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5037-5044, 2020

Authors: Gao, Yu | Pan, Yinsong | Huang, Hong | Mohamed, Ehab R. | Aly, Zahraa M.I.

Article Type: Research Article

Abstract: Hyperspectral remote sensing combines spectrum, ground space and images organically to provide humans with unprecedented rich information. However, a prominent problem faced in the extraction and identification of hyperspectral remote sensing information is mixed pixels, and the method to solve mixed pixels is mixed pixel decomposition. The purpose of this paper is to study the swarm intelligence algorithm of spatial-spectral feature extraction and mixed pixel decomposition of hyperspectral remote sensing images. This paper first introduces two different methods for extracting spatial spectrum features, then studies linear and non-linear spectral hybrid models, and then studies end element extraction methods based on …quantum particle swarm optimization. The degree inversion method, the experimental part is based on the accuracy of the quantum particle swarm optimization-based end-element extraction method and two spatial-spectrum feature extraction methods. The experimental results show that the algorithm proposed in this paper improves the effect of group pixel decomposition based on the swarm intelligence algorithm. The classification accuracy of the 3DLBP spatial spectrum feature proposed in this paper is 94.22%. Show more

Keywords: Hyperspectral remote sensing image, spatial spectral feature extraction, mixed pixel decomposition, swarm intelligence algorithm, abundance inversion

DOI: 10.3233/JIFS-179990

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5045-5055, 2020

Authors: Bi, Shengqin

Article Type: Research Article

Abstract: In the process of globalization, machine translation has undergone a long period of evolution and development. Although the development level of machine translation has been greatly improved, the quality of machine translation is still not very high, and it is difficult to meet the needs of users. Artificial intelligence is the science that studies the laws of human intelligent activity. The application of artificial intelligence technology in the English depression and depression, combined with the Internet and intelligent knowledge base, can develop English translation systems to solve the problem of English translation to a certain extent. Based on the above …background, the research content of this article is a neural network-based artificial intelligence technology English translation system based on the intelligent knowledge base. This article is mainly based on the existing English-Chinese machine translation to find a more favorable method for English long sentence translation. By improving part-of-speech tagging and rules, the rules can match more sentence patterns to improve the quality of existing machine translations. This paper proposes an improved hybrid recommendation algorithm, and through experimental simulation, the results show that the accuracy of the algorithm is not very high. The highest is 35.64%. The possible reason may be that the k value is selected during k-means text clustering, or the N value recommended by TopN is not selected properly, but the hybrid recommendation is still better than ordinary collaborative filtering. Show more

Keywords: Intelligent knowledge base, neural network, artificial intelligence, English translation system, hybrid recommendation algorithm

DOI: 10.3233/JIFS-179991

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5057-5066, 2020

Authors: Wu, Chunqiong | Yu, Rongrui | Yan, Bingwen | Huang, Zhangshu | Yu, Baoqin | Yu, Yanliang | Chen, Na | Zhou, Xiukao

Article Type: Research Article

Abstract: The IoT and Artificial intelligence, the amount of information generated on the Web site is increasing. The rise of the Hadoop distributed cloud computing platform (HDCCP) makes it possible to use multiple computing nodes for parallel computing to solve the performance problems of traditional serial algorithms. The purpose of this paper is to study data design based on cloud computing and improved k-means algorithm (KMA). This paper deeply researches Hadoop distributed cloud computing platform and clustering algorithm and other related technologies, and designs and implements a cluster analysis system (CAS) based on HP. And through an in-depth analysis of the …problems existing in the KMA, an improved scheme based on the HDP is designed. The experimental environment was conFig.d with the cluster analysis system implemented. Finally, the improved KMPA was tested experimentally from four directions: convergence speed, acceleration ratio, initialization sampling rate, and accuracy rate. We can see the experimental results that the CAS based on the HDCCP designed in this paper can provide efficient and configurable cluster analysis services. In this paper, the correct rate is 90.7%. Show more

Keywords: Cloud computing, k-Means algorithm, cluster analysis, hadoop platform, data design

DOI: 10.3233/JIFS-179992

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5067-5074, 2020

Authors: Li, Yan | Hu, Miao | Wang, Taiyong

Article Type: Research Article

Abstract: Welding is an important method for modern material processing. In actual processing, due to the influence of processing accuracy and welding thermal deformation, various defects often appear in the appearance of the weld. At present, visual inspection is mainly used for the appearance inspection of welds. The detection of weld defects mainly depends on the work experience of the staff. Based on the above background, the purpose of this article is to visually inspect the weld surface quality. This article uses visually obtained fringe images of weld contours as information sources to explore a visual-based weld appearance detection algorithm, including …the measurement of weld formation dimensions and the detection of weld appearance defects. This algorithm overcomes manual measurements of the misjudgments and omissions caused by eye fatigue and experience differences. It improves the efficiency and accuracy of welding appearance inspection, and meets the needs of automation and intelligence of the entire welding process. In this paper, a subpixel stripe centerline extraction algorithm based on the combination of the Hessian matrix method and the center of gravity method is used; to further improve the accuracy of the extraction of the centerline of the weld seam, this article also performs the work of removing the wrong points and the compensation of the broken seam. Obtain a fringe centerline with better connectivity. Comparing the extraction algorithms of each centerline, the centerline obtained by this method has high accuracy, less time-consuming and high stability. It laid the foundation for the subsequent inspection of weld appearance. Through the training of the model, the accurate classification and recognition of surface defects of tube and plate welds have been achieved. The experimental results show that the improved vision-based welding surface defect recognition and classification proposed in this paper has better performance and accuracy. Up to 96.34%. Show more

Keywords: Weld quality inspection, machine vision, weld forming size, surface reconstruction, visual inspection

DOI: 10.3233/JIFS-179993

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5075-5084, 2020

Authors: Wu, Yanhong | Dai, Xiuqing

Article Type: Research Article

Abstract: The more and more developed network has caused more and more impact on people’s life and work, providing convenient channels for people’s information exchange, and then improving people’s living and working conditions. However, when data is transmitted through the network, there are hidden security risks, especially important accounting data. Once intercepted and used by criminals, it may cause serious harm to the owner of the data. Based on the above background, the purpose of this article is to study the use of the DES algorithm to encrypt accounting data in a computing environment. This paper proposes an improved quantum genetic …algorithm and applies it to the S-box design of the DES algorithm, which improves the non-linearity of the S-box, reduces the differential uniformity, and enhances the security of the DES algorithm. This improved DES algorithm reduces the number of iterations by increasing the key length and iterative processing using a two-round function, which further increases the security of the algorithm and improves the operation speed of the encryption process. It is found that the 64 ciphertexts of the DES algorithm and the number of changed bits compared to the original ciphertext fluctuates around 32 bits, which explains the problems that should be paid attention to when using the DES algorithm to encrypt accounting data. The validity of key characters should be guaranteed to prevent key loss or leakage. Shorter data encryption regular solution. Show more

Keywords: DES algorithm, accounting data, data encryption, encryption algorithm

DOI: 10.3233/JIFS-179994

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5085-5095, 2020

Authors: Zhang, Long | Liu, Leyi | Chai, Bailong | Xu, Man | Song, Yuhong

Article Type: Research Article

Abstract: Cultural landscapes are cultural property and they are an illustration of the evolution of human society and the living environment over time. As cultural landscape is being valued more and more, the use of 3D modeling is becoming more and more important. As for the 3D reconstruction technology, most of the current methods are complicated in terms of network construction, use, and storage, and then affect the reconstruction efficiency of subsequent cultural landscape heritage. To obtain the 3D reconstruction technology with high reconstruction efficiency, this paper combines the circumferential binary feature extraction algorithm and cloud computing technology, and proposes a …circumferential binary feature extraction and matching search method. The interior-point rate of the CBD algorithm in this paper is greater than 72%, which is higher than the interior point rate of other different algorithms, which indicates that the CBD algorithm in this paper is suitable for matching HD rotated images. The experimental results show that the circular binary features extracted by the article have strong adaptability and fast contrast rate. To better the 3D reconstruction of cultural landscape heritage in the later period, this paper also improves the 4PSC point cloud rough registration algorithm. The experimental results show that compared with other coarse registration algorithms, the improved point cloud coarse registration algorithm improves the registration accuracy and the registration effect is good, which proves the effectiveness of the algorithm. Show more

Keywords: Cloud computing technology, 3D reconstruction, circular binary feature extraction, high-definition image data, point cloud coarse registration, cultural landscape

DOI: 10.3233/JIFS-179995

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5097-5107, 2020

Authors: Zhang, Yubao

Article Type: Research Article

Abstract: The purpose of this article is to explore effective image feature extraction algorithms in the context of big data, and to mine their potential information from complex image data. Based on the BRISK and SIFT algorithms, this paper proposes an image feature extraction and matching algorithm based on BRISK corner points. By combining the SIFT scale space and the BRISK algorithm, a new scale space construction method is proposed. The BRISK algorithm extracts the corner invariant features. Then, by using the improved feature matching method and eliminating the mismatching algorithm, the exact matching of the images is realized. A large …number of experimental verifications were performed in the standard test Mikolajczyk image database and aerial image database. The experimental results show that the improved algorithm in this paper is an effective image matching algorithm. The highest accuracy of actual aerial image matching can reach 85.19%, and it can realize the actual aerial image matching that BRISK and SIFT algorithms cannot complete. The improved algorithm in this paper has the advantages of higher matching accuracy and strong robustness. Show more

Keywords: Big data, image feature extraction, corner point, brisk algorithm, sift algorithm

DOI: 10.3233/JIFS-179996

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5109-5118, 2020