Abstract
We present here the development of a texture-like measure to aid the quantification of rock face stability using two familiar transforms in a novel combination. It is shown that the Fourier and Hough transforms together can yield accurate quantitative information relating to the texture of an image. With respect to rock faces, the textural quality of the image is a direct measure of the stability index, since the orientation, distribution, and number of fissures indicate its stability. Stability of rock faces for mining operations is currently estimated manually, prior to further excavation. Manual inspection is often undesirable due to the subjective nature of, and potential hazard to, the human inspector. This provides the motivation to develop an automated system which can survey the scene via some sensors and process the resulting data to compute a preliminary stability index before further detailed inspection and subsequent excavation. We present in this paper experimental results from real images of local rock faces that demonstrate the viability of this technique.
Original language | English (US) |
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Pages (from-to) | 93-104 |
Number of pages | 12 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 2347 |
DOIs | |
State | Published - Oct 3 1994 |
Event | Machine Vision Applications, Architectures, and Systems Integration III 1994 - Boston, United States Duration: Oct 31 1994 → Nov 4 1994 |
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering