3D Reconstruction using convolution smooth method

Sofyan Arifianto, Hardianto Wibowo, Wildan Suharso, Raditya Novidianto, Dani Harmanto


3D imagery is an image with depth data. The use of depth information in 3D images still has many drawbacks, especially in the image results. Raw data on the 3D camera even does not look smooth, and there is too much noise. Noise in the 3D image is in the form of imprecise data, which results in a rough image. This research will use the convolution smooth methods to improve the 3D image. Will smooth noise in the 3D image, so the resulting image will be better. This smoothing system is called the blurring effect. This research has been tested on flat objects and objects with a circle contour. The test results on the flat surface obtained a distance of 1.3177, the test in the object with a flat surface obtained a distance of 0.4937, and the test in circle contour obtained a distance of 0.3986. This research found that the 3D image will be better after applying the convolution smooth method.


3D image; Convolution smooth; Image reconstruction;

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DOI: https://doi.org/10.11591/eei.v10i3.1991


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