Structured region growing and recognition algorithm for nondestructive evaluation

Jaroslaw P. Sacha; Behrouz N. Shabestari; Krzysztof J. Cios

doi:10.1117/12.258275

14 November 1996 Structured region growing and recognition algorithm for nondestructive evaluation

Jaroslaw P. Sacha, Behrouz N. Shabestari, Krzysztof J. Cios

Proceedings Volume 2847, Applications of Digital Image Processing XIX; (1996) https://doi.org/10.1117/12.258275
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

A novel syntactic region growing and recognition algorithm called SRG will be presented. The primary function of SRG algorithm is detection of structured regions of interest in given image. The recognition technique operates on region's elected features, it is a subject of the next paper. The SRG algorithm can be outlined as follows. Preprocessing is performed to isolate the kernels of potential regions. The first level regions are grown until the region transition are detected. Regions sharing the same transition boundary are merged. The second level regions are grown and merged if they are within the same transition boundary. Growing process is repeated as necessary until whole image or specified region of interest is covered. Features such as area, depth, and others, are computed for each level region and are used for recognition. The recognition is based on region features without regard to region level. The algorithm was designed for analysis of nondestructive evaluation images. In particular, it was successfully tested on x-ray images and on ultrasonic contact scan images of ceramic specimens for detection of microstructural defects. The results of these tests are included in the paper.

Citation Download Citation

Jaroslaw P. Sacha, Behrouz N. Shabestari, and Krzysztof J. Cios "Structured region growing and recognition algorithm for nondestructive evaluation", Proc. SPIE 2847, Applications of Digital Image Processing XIX, (14 November 1996); https://doi.org/10.1117/12.258275

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