scholarly journals Research on the Infrared Thermographic Detection of Concrete under Solar Heating

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dan Zheng ◽  
Shuaishuai Tan ◽  
Xinxin Li ◽  
Haonan Cai

Infrared thermography for detecting defects in concrete structures is closely related to the heat source and the optimized method of the thermal image. Due to the limitation of the irradiation area of the heat source, it is inefficient to detect the defects in large concrete structures. In this paper, sunlight was employed as a heat source to detect the defects with different sizes and depths in concrete, and the measured infrared images were processed and optimized by an enhancement algorithm. The experimental results showed that the defects in concrete could be rapidly identified under sunlight. The effect of environment, view angle, and boundary can be eliminated by image preprocessing, and the histogram equalization algorithm can increase the detection depth of the defects. The research results can also provide a reference for the infrared detection technology of concrete under the weak heat source.

2012 ◽  
Vol 461 ◽  
pp. 215-219
Author(s):  
Yu Qian Zhao ◽  
Zhi Gang Li

According to the characteristics of infrared images, a contrast enhancement algorithm was presented. The principium of FPGA-based adaptive bidirectional plateau histogram equalization was given in this paper. The plateau value was obtained by finding local maximum and whole maximum in statistical histogram based on dimensional histogram statistic. Statistical histogram was modified by the plateau value and balanced in gray scale and gray spacing. Test data generated by single frame image, which was simulated by FPGA-based real-time adaptive bidirectional plateau histogram equalization. The simulation results indicates that the precept meet the requests well in both the image processing effects and processing speed


2013 ◽  
Vol 321-324 ◽  
pp. 1133-1137
Author(s):  
Yu Ting Song ◽  
Xiu Hua Ji ◽  
Shi Lin Zhao

This paper proposes an improved color image enhancement algorithm based on 3-D color histogram equalization algorithm. When the existed 3-D color histogram equalization algorithms in the literatures are applied in processing dim color images, the processed color images often turn pale due to the decrease of color-saturations and have false contours due to gray-scale merging phenomenon in the histogram equalization algorithm. In this paper, the proposed algorithm can make more pixels of the processed color images keep their color-saturations and reduce the gray-scale merging with Logarithmic histogram equalization algorithm. Test results with dim color images present a better effect of image enhancement.


2012 ◽  
Vol 505 ◽  
pp. 263-266
Author(s):  
Dong Mei Liu ◽  
Tao Zhang ◽  
Chuan Li Yin ◽  
Xiao Qiang Ji

According to the disadvantage of the large noises of histogram equalization algorithm, a new adaptive image enhancement algorithm is presented. First, the statistical histogram of the infrared image is done. Then the threshold of plateaus Equalization is calculated and the statistical histogram is modified. Finally the bright values of the pixels of the image are changed. An embedded high speed image enhancement processing system on high performance DSP TMS320DM642 and FPGA was designed. Experimental results with real images shown that the system can improve the contrast of the infrared image, limit the noises of the enhancement image, and effectively enhance the infrared image, the running time of the program is shorter, so it can meet the requirements of real-time in the project.


2012 ◽  
Vol 201-202 ◽  
pp. 91-94
Author(s):  
Yan Xi Zhang ◽  
Xiang Dong Gao

Configuration of a molten pool is related to the laser welding quality. Analyzing the configuration of a molten pool is important to monitor the laser welding process. This paper proposes a method of segmentation of a molten pool and its shadow during high power disk laser welding, consequently provides the groundwork for reconstruction of the molten pool and analysis of welding quality. Subsection linear stretching histogram equalization was applied to enhance the contrast of the original images firstly, and then edge detection was used to highlight the edges. After that we used the morphology filtering method to produce the segmentation mask, and then combined the mask with the original images to get the final segmentation results. Also, the proposed method was compared with other traditional methods. The experimental results showed that our method not only could give better segmentation results and process large quantities images automatically, but also overcame the less-segmentation problems of traditional methods.


Author(s):  
Ridha Ilyas Bendjillali ◽  
Mohammed Beladgham ◽  
Khaled Merit ◽  
Abdelmalik Taleb-Ahmed

<p><span>In the last decade, facial recognition techniques are considered the most important fields of research in biometric technology. In this research paper, we present a Face Recognition (FR) system divided into three steps: The Viola-Jones face detection algorithm, facial image enhancement using Modified Contrast Limited Adaptive Histogram Equalization algorithm (M-CLAHE), and feature learning for classification. For learning the features followed by classification we used VGG16, ResNet50 and Inception-v3 Convolutional Neural Networks (CNN) architectures for the proposed system. Our experimental work was performed on the Extended Yale B database and CMU PIE face database. Finally, the comparison with the other methods on both databases shows the robustness and effectiveness of the proposed approach. Where the Inception-v3 architecture has achieved a rate of 99, 44% and 99, 89% respectively.</span></p>


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