In order to realize automatic weld seam tracking for pipeline ultrasonic flaw inspection, an image processing algorithm based on HSI color space was presented. Since the color tones of weld seam were different from th...In order to realize automatic weld seam tracking for pipeline ultrasonic flaw inspection, an image processing algorithm based on HSI color space was presented. Since the color tones of weld seam were different from the parent metal, weld seam images were transformed to HSI color space. In the HSl colar space, the weld seam and base metal area can be apparently distinguished. By using this image processing algorithm, the edges and centerline of pipeline weld seam can be correctly extracted. An industrial application system was developed based on the image processing algorithm, and the image processing time is less than 70 ms and the accuracy of weld seam recognition is better than 2mm.展开更多
A method based on HSI color space is presented to solve the problem of circle detection from color images. In terms of the evaluation to the edge detection method based on intensity, the edge detection based on hue is...A method based on HSI color space is presented to solve the problem of circle detection from color images. In terms of the evaluation to the edge detection method based on intensity, the edge detection based on hue is chosen to process the color image, and the simplified calculation of hue transform is discussed. Then the algorithm of circle detection based on Canny edge detection is proposed. Due to the dispersive distribution of the detected result, Hough transformation and template smooth are used in circle detection, and the proposed method gives a quite good result.展开更多
The traditional single image dehazing algorithm is susceptible to the prior knowledge of hazy image and colour distortion.A new method of deep learning multi-scale convolution neural network based on HSI colour space ...The traditional single image dehazing algorithm is susceptible to the prior knowledge of hazy image and colour distortion.A new method of deep learning multi-scale convolution neural network based on HSI colour space for single image dehazing is proposed in this paper,which directly learns the mapping relationship between hazy image and corresponding clear image in colour,saturation and brightness by the designed structure of deep learning network to achieve haze removal.Firstly,the hazy image is transformed from RGB colour space to HSI colour space.Secondly,an end-to-end multi-scale full convolution neural network model is designed.The multi-scale extraction is realized by three different dehazing sub-networks:hue H,saturation S and intensity I,and the mapping relationship between hazy image and clear image is obtained by deep learning.Finally,the model was trained and tested with hazy data set.The experimental results show that this method can achieve good dehazing effect for both synthetic hazy images and real hazy images,and is superior to other contrast algorithms in subjective and objective evaluations.展开更多
文摘In order to realize automatic weld seam tracking for pipeline ultrasonic flaw inspection, an image processing algorithm based on HSI color space was presented. Since the color tones of weld seam were different from the parent metal, weld seam images were transformed to HSI color space. In the HSl colar space, the weld seam and base metal area can be apparently distinguished. By using this image processing algorithm, the edges and centerline of pipeline weld seam can be correctly extracted. An industrial application system was developed based on the image processing algorithm, and the image processing time is less than 70 ms and the accuracy of weld seam recognition is better than 2mm.
文摘A method based on HSI color space is presented to solve the problem of circle detection from color images. In terms of the evaluation to the edge detection method based on intensity, the edge detection based on hue is chosen to process the color image, and the simplified calculation of hue transform is discussed. Then the algorithm of circle detection based on Canny edge detection is proposed. Due to the dispersive distribution of the detected result, Hough transformation and template smooth are used in circle detection, and the proposed method gives a quite good result.
基金National Natural Science Foundation of China(No.61963023)MOE(Ministry of Education in China)Project of Humanities and Social Sciences(No.19YJC760012)。
文摘The traditional single image dehazing algorithm is susceptible to the prior knowledge of hazy image and colour distortion.A new method of deep learning multi-scale convolution neural network based on HSI colour space for single image dehazing is proposed in this paper,which directly learns the mapping relationship between hazy image and corresponding clear image in colour,saturation and brightness by the designed structure of deep learning network to achieve haze removal.Firstly,the hazy image is transformed from RGB colour space to HSI colour space.Secondly,an end-to-end multi-scale full convolution neural network model is designed.The multi-scale extraction is realized by three different dehazing sub-networks:hue H,saturation S and intensity I,and the mapping relationship between hazy image and clear image is obtained by deep learning.Finally,the model was trained and tested with hazy data set.The experimental results show that this method can achieve good dehazing effect for both synthetic hazy images and real hazy images,and is superior to other contrast algorithms in subjective and objective evaluations.
