The geometric and motion characteristics of false targets are more similar to those of real targets. The detection accuracy of traditional infrared radiation characteristics methods for infrared targets is obviously low. For small infrared weak targets with small size and low signal-to-noise ratio, it is difficult to effectively extract shape features by using a single band detection method. Therefore, this paper makes full use of the advantages of infrared single band image and multispectral image target detection methods, and combines single band detection technology and multispectral detection technology, which not only avoids the defect of single band detection missing alarm, but also reduces the impact of large amount of multispectral detection data, and has real-time performance and good detection effect. The hybrid detection algorithm proposed in this paper has stronger adaptability, higher recognition rate and faster processing ability.
This paper studies a method of detecting the position of crankshaft flange hole group based on vision measurement, and sets up the position detection system of crankshaft flange hole group. The relative measurement model of hole group position is established by using the standard crankshaft information, and the system calibration method is studied. In this paper, a multi-camera calibration method based on polynomial fitting two-dimensional image mapping model is adopted. In addition, the image processing technology of hole group is studied. The improved Canny edge detection method is used to extract the contour of the hole group. Redundant edge filtering algorithm is used to eliminate unreliable edges. Then use the gradient interpolation method to extract sub-pixel edges. The measurement results show that the single-direction measurement error of the central coordinate of the crankshaft flange hole group is less than 0.07mm, and the repeatability error is less than 0.009mm, which provides a basis for the realization of industrial online efficient detection.
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