• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.4
• /
• pp.499-505
• /
• 1998

In developing an automated surface inspect algorithm, we have designed a hierarchical classifier using neural network. The defects which exist on the surface of cold mill strip have a scattering or singular distribution. We have considered three major problems, that is preprocessing, feature extraction and defect classification. In preprocessing, Top-hit transform, adaptive thresholding, thinning and noise rejection are used Especially, Top-hit transform using local minimax operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, and histogram ratio features are calculated. The histogram ratio feature is taken from the gray-level image. For defect classification, we suggest a hierarchical structure of which nodes are multilayer neural network classifiers. The proposed algorithm reduced error rate by comparing to one-stage structure.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.2
• /
• pp.179-186
• /
• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.365-370
• /
• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

• Journal of the Korean Geotechnical Society
• /
• v.37 no.11
• /
• pp.51-60
• /
• 2021

River scour erodes the soil around the pier, reducing the lateral bearing capacity of the pier and lowering the stability of the structure. In this study, in order to examine the effect of scouring on the stability of the structure, an experiment was performed to measure the natural frequency of the pier according to the excavation of the surrounding ground. Impact vibration test was conducted on the pier with the caisson foundation of the Mangyeonggang Bridge, which is scheduled to be demolished. Accelerometers were attached to the top, center, and bottom of the pier and the acceleration responses were measured by hitting those three points. The experimental results showed that the top hit showed consistent and reasonable results of the acceleration responses according to the hitting position. The measured accelerations were converted to the frequency domain through Fast Fourier Transform (FFT), and then the natural frequency was determined. In addition, to analyze the scour effect on the natural frequency of the pier, the ground around the pier was excavated and the natural frequency change was analyzed. As a result, the natural frequency showed the decreasing tendency according to the excavation depth, but the decrease was small due to the large stiffness of the caisson foundation.