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  • Open Access

    ARTICLE

    Research on Concrete Beam Crack Recognition Algorithm Based on Block Threshold Value Image Processing

    Wenting Qiao1,2, Xiaoguang Wu1,*, Wen Sun3, Qiande Wu4,*

    Structural Durability & Health Monitoring, Vol.14, No.4, pp. 355-374, 2020, DOI:10.32604/sdhm.2020.011479 - 04 December 2020

    Abstract To solve the problem that the digital image recognition accuracy of concrete structure cracks is not high under the condition of uneven illumination and complex surface color of concrete structure, this paper has proposed a block segmentation method of maximum entropy threshold based on the digital image data obtained by the ACTIS automatic detection system. The steps in this research are as follows: 1. The crack digital images of concrete specimens with typical features were collected by using the Actis system of KURABO Co., Ltd., of Japan in the concrete beam bending test. 2. The… More >

  • Open Access

    ARTICLE

    Pattern Recognition of Construction Bidding System Based on Image Processing

    Xianzhe Zhang1,3,∗, Sheng Zhou2,†, Jun Fang1,‡, Yanling Ni3,§

    Computer Systems Science and Engineering, Vol.35, No.4, pp. 247-256, 2020, DOI:10.32604/csse.2020.35.247

    Abstract Bidding for construction projects is a very important and representative field in the industry. The system of bidding for construction projects has made considerable progress over the years due to the accumulation of experience and many contributions to the field. Nowadays, with the rapid development of information technology and the intellectualization of the bidding system for construction projects, the accumulation and processing of data has become an essential element of its development. In order to manage the bidding system of construction engineering reasonably, this paper proposes a system based on image processing and pattern recognition… More >

  • Open Access

    ARTICLE

    Application Research of Color Design and Collocation in Image Processing

    Feiying Xia1, Shenghong Huang2,*

    Computer Systems Science and Engineering, Vol.35, No.2, pp. 91-98, 2020, DOI:10.32604/csse.2020.35.098

    Abstract Color is one of the primary elements of artistic expression. Its design and collocation play a very important role in image processing. While the number of people using the Internet is increasing, more attention is being paid to the user’s experience including the color design and matching of the Internet web interface, in order to reach the color design of the web interface with image processing as the core. This thesis firstly discusses the importance of web interface color design and matching in image processing from the image processing appeal of the web interface and More >

  • Open Access

    ARTICLE

    Enhanced GPU-Based Anti-Noise Hybrid Edge Detection Method

    Sa’ed Abed, Mohammed H. Ali, Mohammad Al-Shayeji

    Computer Systems Science and Engineering, Vol.35, No.1, pp. 21-37, 2020, DOI:10.32604/csse.2020.35.021

    Abstract Today, there is a growing demand for computer vision and image processing in different areas and applications such as military surveillance, and biological and medical imaging. Edge detection is a vital image processing technique used as a pre-processing step in many computer vision algorithms. However, the presence of noise makes the edge detection task more challenging; therefore, an image restoration technique is needed to tackle this obstacle by presenting an adaptive solution. As the complexity of processing is rising due to recent high-definition technologies, the expanse of data attained by the image is increasing dramatically.… More >

  • Open Access

    ARTICLE

    Automated Inspection of Char Morphologies in Colombian Coals Using Image Analysis

    Deisy Chaves1,5,*, Maria Trujillo1, Edward Garcia2, Juan Barraza2, Edward Lester3, Maribel Barajas4, Billy Rodriguez4, Manuel Romero4, Laura Fernández-Robles5

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 397-405, 2020, DOI:10.32604/iasc.2020.013916

    Abstract Precise automated determination of char morphologies formed by coal during combustion can lead to more efficient industrial control systems for coal combustion. Commonly, char particles are manually classified following the ICCP decision tree which considers four morphological features. One of these features is unfused material, and this class of material not characteristic of Colombian coals. In this paper, we propose new machine learning algorithms to classify the char particles in an image based system. Our hypothesis is that supervised classification methods can outperform the 4 ‘class’ ICCP criteria. In this paper we evaluate several morphological More >

  • Open Access

    ARTICLE

    Edge Detection Based on Generative Adversarial Networks

    Xiaoyan Chen, Jiahuan Chen*, Zhongcheng Sha

    Journal of New Media, Vol.2, No.2, pp. 61-77, 2020, DOI:10.32604/jnm.2020.010062 - 21 August 2020

    Abstract Aiming at the problem that the detection effect of traditional edge detection algorithm is not good, and the problem that the existing edge detection algorithm based on convolution network cannot solve the thick edge problem from the model itself, this paper proposes a new edge detection method based on the generative adversarial network. The confrontation network consists of generator network and discriminator network, generator network is composed of U-net network and discriminator network is composed of five-layer convolution network. In this paper, we use BSDS500 training data set to train the model. Finally, several images More >

  • Open Access

    ARTICLE

    Image Processing of Manganese Nodules Based on Background Gray Value Calculation

    Hade Mao1, 2, Yuliang Liu1, 2, *, Hongzhe Yan1, 2, Cheng Qian3, Jing Xue4

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 511-527, 2020, DOI:10.32604/cmc.2020.09841 - 23 July 2020

    Abstract To troubleshoot two problems arising from the segmentation of manganese nodule images-uneven illumination and morphological defects caused by white sand coverage, we propose, with reference to features of manganese nodules, a method called “background gray value calculation”. As the result of the image procession with the aid this method, the two problems above are solved eventually, together with acquisition of a segmentable image of manganese nodules. As a result, its comparison with other segmentation methods justifies its feasibility and stability. Judging from simulation results, it is indicated that this method is applicable to repair the More >

  • Open Access

    ARTICLE

    Survey on the Application of Deep Reinforcement Learning in Image Processing

    Wei Fang1, 2, 3, ∗, Lin Pang1, Weinan Yi1

    Journal on Artificial Intelligence, Vol.2, No.1, pp. 39-58, 2020, DOI:10.32604/jai.2020.09789 - 15 July 2020

    Abstract In recent years, with the rapid development of human society, more and more complex tasks have emerged that require deep learning to automatically extract abstract feature representations from a large amount of data, and use reinforcement learning to learn the best strategy to complete the task. Through the combination of deep learning and reinforcement learning, end-to-end input and output can be achieved, and substantial breakthroughs have been made in many planning and decision-making systems with infinite states, such as games, in particular, AlphaGo, robotics, natural language processing, dialogue systems, machine translation, and computer vision. In More >

  • Open Access

    ARTICLE

    An Efficient Bar Code Image Recognition Algorithm for Sorting System

    Desheng Zheng1, *, Ziyong Ran1, Zhifeng Liu1, Liang Li2, Lulu Tian3

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1885-1895, 2020, DOI:10.32604/cmc.2020.010070 - 30 June 2020

    Abstract In the sorting system of the production line, the object movement, fixed angle of view, light intensity and other reasons lead to obscure blurred images. It results in bar code recognition rate being low and real time being poor. Aiming at the above problems, a progressive bar code compressed recognition algorithm is proposed. First, assuming that the source image is not tilted, use the direct recognition method to quickly identify the compressed source image. Failure indicates that the compression ratio is improper or the image is skewed. Then, the source image is enhanced to identify More >

  • Open Access

    ARTICLE

    A Deep Convolutional Architectural Framework for Radiograph Image Processing at Bit Plane Level for Gender & Age Assessment

    N. Shobha Rani1, *, M. Chandrajith2, B. R. Pushpa1, B. J. Bipin Nair1

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 679-694, 2020, DOI:10.32604/cmc.2020.08552

    Abstract Assessing the age of an individual via bones serves as a fool proof method in true determination of individual skills. Several attempts are reported in the past for assessment of chronological age of an individual based on variety of discriminative features found in wrist radiograph images. The permutation and combination of these features realized satisfactory accuracies for a set of limited groups. In this paper, assessment of gender for individuals of chronological age between 1-17 years is performed using left hand wrist radiograph images. A fully automated approach is proposed for removal of noise persisted… More >

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