A Cumulative Sums Algorithm for Segmentation of Digital X-ray Images

Abstract

A mathematical model of digital X-ray image of the test object is presented for the case when the main type of image distortion is the noise due to the quantum nature of the radiation. The new multilevel cumulative sums algorithm for automatic image segmentation is proposed. The algorithm is based on the edge detection of the segments homogeneous in brightness along the image rows and columns by repeatedly applying the cumulative sums procedure. The efficiency of the proposed algorithm is compared with the known threshold and Leader algorithms. The comparison was performed on simulated images as well as on the X-ray image of a weld. The mean square errors for the new algorithm were about two and three times less than for the threshold and Leader algorithms, correspondingly.

Original language	English
Article number	78
Journal	Journal of Nondestructive Evaluation
Volume	38
Issue number	3
DOIs	https://doi.org/10.1007/s10921-019-0616-3
Publication status	Published - 1 Sep 2019

Keywords

Digital X-ray image
Inspected object
Mathematical model
Segmentation algorithms

ASJC Scopus subject areas

Mechanics of Materials
Mechanical Engineering

Access to Document

10.1007/s10921-019-0616-3

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Vorobeychikov, S. E., Chakhlov, S. V., & Udod, V. A. (2019). A Cumulative Sums Algorithm for Segmentation of Digital X-ray Images. Journal of Nondestructive Evaluation, 38(3), [78]. https://doi.org/10.1007/s10921-019-0616-3

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abstract = "A mathematical model of digital X-ray image of the test object is presented for the case when the main type of image distortion is the noise due to the quantum nature of the radiation. The new multilevel cumulative sums algorithm for automatic image segmentation is proposed. The algorithm is based on the edge detection of the segments homogeneous in brightness along the image rows and columns by repeatedly applying the cumulative sums procedure. The efficiency of the proposed algorithm is compared with the known threshold and Leader algorithms. The comparison was performed on simulated images as well as on the X-ray image of a weld. The mean square errors for the new algorithm were about two and three times less than for the threshold and Leader algorithms, correspondingly.",

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