3-D radiographic methodology has been into the spotlight for quality inspection of mass product or in-service inspection of aging product. To locate a target object in 3-D space, its characteristic contours such as edge length, edge angle, and vertices are very important. In spite of a simple geometry product, it is very difficult to get clear shape contours from a single radiographic image. The image contains scattering noise at the edges and ambiguity coming from X-Ray absorption within the body. This article suggests a concise method to extract whole edges from a single X-ray image. At the edge point of the object, the intensity of the X-ray decays exponentially as the X-ray penetrates the object. Considering this X-Ray decaying property, edges are extracted by using the least square fitting with the control of Coefficient of Determination.

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X-ray images are heavily affected by noise which makes normal image processing not workable. This paper suggested a new method to identify the primary 3-D shape of an embedded object and its pose by using only single X-ray image. The image feature consists of corner points and edge/intersection lines of adjacent surfaces. The intensity of an X-ray image is attenuated exponentially with increasing the penetration thickness. The main finding is to model a precise exponential relationship to fit the variation of X-ray image intensity. It applied a least-square-method to the X-ray projection image and effectively extracted edges and intersection lines from the noise of X-ray image.