Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (8)
  • Open Access

    ARTICLE

    A Novel Filtering-Based Detection Method for Small Targets in Infrared Images

    Sanxia Shi, Yinglei Song*

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2911-2934, 2024, DOI:10.32604/cmc.2024.055363 - 18 November 2024

    Abstract Infrared small target detection technology plays a pivotal role in critical military applications, including early warning systems and precision guidance for missiles and other defense mechanisms. Nevertheless, existing traditional methods face several significant challenges, including low background suppression ability, low detection rates, and high false alarm rates when identifying infrared small targets in complex environments. This paper proposes a novel infrared small target detection method based on a transformed Gaussian filter kernel and clustering approach. The method provides improved background suppression and detection accuracy compared to traditional techniques while maintaining simplicity and lower computational costs.… More >

  • Open Access

    ARTICLE

    Research on Defect Detection of Wind Turbine Blades Based on Morphology and Improved Otsu Algorithm Using Infrared Images

    Shuang Kang1, Yinchao He1,2, Wenwen Li1,*, Sen Liu2

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 933-949, 2024, DOI:10.32604/cmc.2024.056614 - 15 October 2024

    Abstract To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades (WTB), this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm. First, mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image. The algorithm employs entropy as the objective function to guide the iteration process of image enhancement, selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations, effectively enhancing the detail features of defect… More >

  • Open Access

    ARTICLE

    Infrared and Visible Image Fusion Based on Res2Net-Transformer Automatic Encoding and Decoding

    Chunming Wu1, Wukai Liu2,*, Xin Ma3

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1441-1461, 2024, DOI:10.32604/cmc.2024.048136 - 25 April 2024

    Abstract A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase the visual impression of fused images by improving the quality of infrared and visible light picture fusion. The network comprises an encoder module, fusion layer, decoder module, and edge improvement module. The encoder module utilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformer to achieve deep-level co-extraction of local and global features from the original picture. An edge enhancement module (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy More >

  • Open Access

    ARTICLE

    IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

    Xiao Luo1,3, Hao Zhu1,2,*, Zhenli Zhang1,2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2667-2687, 2024, DOI:10.32604/cmc.2024.047988 - 27 February 2024

    Abstract Road traffic safety can decrease when drivers drive in a low-visibility environment. The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents. To tackle the challenges posed by the low recognition accuracy and the substantial computational burden associated with current infrared pedestrian-vehicle detection methods, an infrared pedestrian-vehicle detection method A proposal is presented, based on an enhanced version of You Only Look Once version 5 (YOLOv5). First, A head specifically designed for detecting small targets has been integrated into… More >

  • Open Access

    ARTICLE

    Efficient Deep Learning Modalities for Object Detection from Infrared Images

    Naglaa F. Soliman1,2, E. A. Alabdulkreem3, Abeer D. Algarni1,*, Ghada M. El Banby4, Fathi E. Abd El-Samie1,5, Ahmed Sedik6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2545-2563, 2022, DOI:10.32604/cmc.2022.020107 - 29 March 2022

    Abstract For military warfare purposes, it is necessary to identify the type of a certain weapon through video stream tracking based on infrared (IR) video frames. Computer vision is a visual search trend that is used to identify objects in images or video frames. For military applications, drones take a main role in surveillance tasks, but they cannot be confident for long-time missions. So, there is a need for such a system, which provides a continuous surveillance task to support the drone mission. Such a system can be called a Hybrid Surveillance System (HSS). This system… More >

  • Open Access

    ARTICLE

    Infrared and Visible Image Fusion Based on NSST and RDN

    Peizhou Yan1, Jiancheng Zou2,*, Zhengzheng Li1, Xin Yang3

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 213-225, 2021, DOI:10.32604/iasc.2021.016201 - 17 March 2021

    Abstract Within the application of driving assistance systems, the detection of driver’s facial features in the cab for a spectrum of luminosities is mission critical. One method that addresses this concern is infrared and visible image fusion. Its purpose is to generate an aggregate image which can granularly and systematically illustrate scene details in a range of lighting conditions. Our study introduces a novel approach to this method with marked improvements. We utilize non-subsampled shearlet transform (NSST) to obtain the low and high frequency sub-bands of infrared and visible imagery. For the low frequency sub-band fusion,… More >

  • Open Access

    ARTICLE

    Intelligent Fusion of Infrared and Visible Image Data Based on Convolutional Sparse Representation and Improved Pulse-Coupled Neural Network

    Jingming Xia1, Yi Lu1, Ling Tan2,*, Ping Jiang3

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 613-624, 2021, DOI:10.32604/cmc.2021.013457 - 12 January 2021

    Abstract Multi-source information can be obtained through the fusion of infrared images and visible light images, which have the characteristics of complementary information. However, the existing acquisition methods of fusion images have disadvantages such as blurred edges, low contrast, and loss of details. Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform (NSST). Furthermore, the low-frequency subbands were fused by convolutional sparse representation (CSR), and the high-frequency subbands were fused by an improved pulse More >

  • Open Access

    ARTICLE

    EXPERIMENTAL STUDY ON WATER CURTAIN FIGHTING FIRE BASED ON INFRARED TECHNIQUE

    Hui Zhong, Guohua Chen* , Saihua Jiang

    Frontiers in Heat and Mass Transfer, Vol.8, pp. 1-5, 2017, DOI:10.5098/hmt.8.17

    Abstract Infrared radiation is a type of electromagnetic radiation and invisible to human eyes. It is used widely in industrial, scientific, and medical applications. Pool fire is an emergent accident, which emits intense thermal radiation. In order to quantify the performance of water curtain fighting fire, a testing platform is built and experimental studies are carried out. An infrared imager is used to acquire real-time experimental data and respond to the variations of flame in time and space dimensions. Experimental principles and operating procedures are described in detail. The transmissivity is used to quantify the performance More >

Displaying 1-10 on page 1 of 8. Per Page