Superpixel Image Segmentation-Based Particle Size Distribution Analysis of Fragmented Rock
| Autor: | Haojie Ding, Zhen Yang, Li Guo, Minjie Lian |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
010504 meteorology & atmospheric sciences
General Computer Science Computer science image denoising Noise reduction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION superpixel generated image 02 engineering and technology 01 natural sciences Texture (geology) Image (mathematics) 0202 electrical engineering electronic engineering information engineering General Materials Science image enhancement Electrical and Electronic Engineering 0105 earth and related environmental sciences business.industry General Engineering Wavelet transform Pattern recognition Image segmentation TK1-9971 Photogrammetry 020201 artificial intelligence & image processing Artificial intelligence Particle size Granularity Electrical engineering. Electronics. Nuclear engineering business Digital image processing granularity distribution |
| Zdroj: | IEEE Access, Vol 9, Pp 59048-59058 (2021) |
| ISSN: | 2169-3536 |
| Popis: | Research on the particle size of blast piles has always been an essential issue in mining engineering. Reasonable blasting parameters can reduce mining costs and reduce the workload of secondary crushing, which can significantly improve mining efficiency. The usual particle size analysis methods include the sieving method, the large particle size statistical method and other manual measurement methods. Nevertheless, these methods have the disadvantages of a high labor intensity, low efficiency and low precision. This paper analyzes UAV image information based on the single-picture photogrammetry method of computer image processing technology. A two-dimensional empirical wavelet transform (EWT) is used for image noise reduction. The nonlocal multiscale fractional differential (NMFD) enhances the texture of dark images and uses superpixel image segmentation technology so that the processed image can meet the granularity statistical study requirements of blast piles. The research results show that the accuracy of the ore particle size distribution by the method proposed in this paper is more than 90%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|