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Jensen, A.M., Baumann, M., Chen, Y.: Low-cost multispectral aerial imaging using autonomous runway-free small flying wing vehicles. Metni, N., Hamel, T.: A UAV for bridge inspection: visual servoing control law with orientation limits. In: Proceedings Sixth IEEE Workshop on Applications of Computer Vision, 2002. Springer, New York (2013)ĭickson, P., Li, J., Zhu, Z., Hanson, A.R., Riseman, E.M., Sabrin, H., Schultz, H., Whitten, G.: Mosaic generation for under vehicle inspection. (eds.) Nondestructive testing of materials and structures, pp. Kumar, S.S., Bharatkumar, B.H., Ramesh, G., Krishnamoorthy, T.S.: Integration of NDT in rapid screening of concrete structures. Zhou, F., Zou, R., Qiu, Y., Gao, H.: Automated visual inspection of angle cocks during train operation. In: IEEE International Conference Intelligent Robots and System, pp. Hansen, P., Alismail, H., Browning, B., Rander, P.: Stereo visual odometry for pipe mapping. While applied to the challenge of reducing specularity in inspection videos, the method improves upon the state-of-the-art in specularity removal, and its applications are wide-ranging as a general purpose pre-processing tool.ĭobie, G., Summan, R., Macleod, C., Pierce, S.G.: NDT & E International Visual odometry and image mosaicing for NDE. The method is shown to work well on greyscale as well as colour images and effectively reduces specularity and significantly improves the quality of the stitched image, even in the presence of noise.
#Metal reflection images free
This results in an image that is free from specular highlights provided there is at least one frame present in the sequence where a given pixel is present in a diffuse form. The technique first automatically determines frames which contain overlapping regions before the relationship that exists between them is exploited in order to suppress the effects of specular reflections. We present a method which exploits additional information in neighbouring frames from video footage to reduce specularity from each frame. Furthermore, they can hide small defects in the images causing them to be missed during inspection. In particular, this poses a significant challenge for applications where image stitching is used to create a single static image of a scene from inspection footage of pipes, gas tubes, train tracks and concrete structures. Then you can stack them and use "if darker" blending mode.The presence of specular highlights can hide underlying features of a scene within an image and can be problematic in many application scenarios. Prepare a setup with two sets of lights than can be turned on and off using different switches, you can simply plug and unplug set 1 and set 2 of continuos lights (you said "of the light bulbs themselves as tiny spots") or using different groups if you are using flashes. Take (at least) two shoots with the camera mounted on a tripod. Moving the lights around, in controlled angles, and using the non reflected zones of each photo. You could use some method of multi-exposure Reflections give shape to forms, it gives you a clue if a shape is flat or curved.
#Metal reflection images how to
You need to learn how to make those reflections a beautiful part of the photo.
Imagine a photo of a car without reflections. Reflections are part of what makes a product shot beautifulĮspecially on glossy materials. There is no way of removing reflections on metallic surfaces.īecause light is not polarized, so there is no way to block using any polarizing filter. The same would apply to a chrome metal lens frame. That can only be made on a computer-generated image. Imagine you are taking a photo of a mirror, eliminating every reflection would mean every mirror will be pitch black. Light bounces, that comes with the concept of Photo-graphy. You can not remove EVERY specular reflection.
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