Surface Defect Detection Model for Aero-Engine Components Based on Improved YOLOv5

Aiming at the problems of low efficiency and poor accuracy in conventional surface defect detection methods for aero-engine components, a surface defect detection model based on an improved YOLOv5 object detection algorithm is proposed in this paper. First, a k-means clustering algorithm was used to recalculate the parameters of the preset anchors to make them match the samples better. Then, an ECA-Net attention mechanism was added at the end of the backbone network to make the model pay more attention to feature extraction from defect areas. Finally, the PANet structure of the neck network was improved through its replacement with BiFPN modules to fully integrate the features of all scales. The results showed that the mAP of the YOLOv5s-KEB model was 98.3%, which was 1.0% higher than the original YOLOv5s model, and the average inference time for a single image was 2.6 ms, which was 10.3% lower than the original model. Moreover, compared with the Faster R-CNN, YOLOv3, YOLOv4 and YOLOv4-tiny object detection algorithms, the YOLOv5s-KEB model has the highest accuracy and the smallest size, which make it very efficient and convenient for practical applications

Generalized Polarimetric Dehazing Method Based on Low-Pass Filtering in Frequency Domain

Polarimetric dehazing methods can significantly enhance the quality of hazy images. However, current methods are not robust enough under different imaging conditions. In this paper, we propose a generalized polarimetric dehazing method based on low-pass filtering in the frequency domain. This method can accurately estimate the polarized state of the scattering light automatically without adjusting bias parameters. Experimental results show the effectiveness and robustness of our proposed method in different hazy weather and scattering underwater environments with different densities. Furthermore, computational efficiency is enhanced more than 70% compared to the polarimetric dehazing method we proposed previously.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Wide-Range Continuously-Tunable Slow-Light Delay Line Based on Stimulated Brillouin Scattering

Through selectively controlling the stimulated Brillouin scattering in optical fibers with different lengths, a continuously tunable time-delay scheme enabling to work in a large range is proposed in this letter. This is realized by connecting a fixed long single-mode fiber (SMF) to one of the several selectable short SMFs that successively have an equal increment in length. These short-length fibers are, respectively, fixed to the different channels between two identical optical switches. Therefore, a wide-range and continuously tunable slow-light delay line can be constructed by changing the power of the pump beam, assisted by switching to different channels. In the experiment, a time delay from 0 to 201.29 ns is demonstrated for a five-channel configuration. A further large-range time delay can be expected if one adds the number of channels accordingly

A robust haze-removal scheme in polarimetric dehazing imaging based on automatic identification of sky region

<p> Quality enhancement of images acquired in hazy conditions is a significant research area in civil and military applications. The polarimetric dehazing methods have been exploited to dehaze hazy images and have proven to be effective in enhancing their quality. In this paper, by combining the polarimetric imaging technique and the dark channel prior technique, a robust haze-removal scheme is presented for the first time. On the one hand, the polarimetric imaging technique has advantages in recovering detailed information well, especially in dense hazy conditions; on the other hand, the dark channel prior technique provides a much more precise and convenient way to estimate the airlight radiance through extracting the sky region automatically. The experiments verify the practicability and effectiveness of the proposed dehazing scheme in quality enhancement of hazy images. Furthermore, comparison study demonstrates that the proposed scheme is superior to some sophisticated methods in terms of the visibility and contrast. We believe this scheme is beneficial in the image dehazing applications, especially for real-time applications. (C) 2016 Elsevier Ltd. All rights reserved.</p