Automatic detection of particle size distribution by image analysis based on local adaptive canny edge detection and modified circular Hough transform. (March 2018)

• Record Type: Journal Article
• Authors: Meng, Yingchao; Zhang, Zhongping; Yin, Huaqiang; Ma, Tao
• Is Part Of: Micron. Volume 106(2018)
• Page Start: 34
• Page End: 41
• Publication Date: 2018-03
• Subjects: Local adaptive Canny edge detection -- Modified circular Hough transform -- Particle size distribution -- Image processing; Microscopy -- Periodicals; Electron Probe Microanalysis -- Periodicals; Microscopy -- Periodicals; Microscopie -- Périodiques; Microscopy; Periodicals; 502.82
• DOI: 10.1016/j.micron.2017.12.002
• Languages: English
• ISSNs: 0968-4328

Abstract

Highlights: Automatic measurement of particle size distribution from micrographs. The proposed algorithm is mainly based on local adaptive Canny edge detection and modified circular Hough transform. The robustness and reliability of the algorithm were verified by several micrographs with different complexity. Abstract: To obtain size distribution of nanoparticles, scanning electron microscope (SEM) and transmission electron microscopy (TEM) have been widely adopted, but manual measurement of statistical size distributions from the SEM or TEM images is time-consuming and labor-intensive. Therefore, automatic detection methods are desirable. This paper proposes an automatic image processing algorithm which is mainly based on local adaptive Canny edge detection and modified circular Hough transform. The proposed algorithm can utilize the local thresholds to detect particles from the images with different degrees of complexity. Compared with the results produced by applying global thresholds, our algorithm performs much better. The robustness and reliability of this method have been verified by comparing its results with manual measurement, and an excellent agreement has been found. The proposed method can accurately recognize the particles with high efficiency.