Xiangqun Song

A method for recognizing particles in overlapped particle images

This paper describes a new method to divide a planar curve into circular arcs in order to recognize the overlapped particles in an image. The segmentation is based on a new breakpoint detection method. An area correlation coefficient for two arcs is introduced to identify and cluster the arcs belonging to the same circle. The Least-Squares Method is applied to estimate the center of a circle and its radius. The present method is evaluated using a computer-generated sample image and real coal-ash images with heavily overlapped particles taken by an electron microscope. All the results showed that the present method is effective in recognizing the overlapped circles with high accuracy.

Velocity and size measurement of falling particles with fuzzy PTV

Abstract This paper describes a method for simultaneously measuring the velocities and sizes of falling particles. The measurement method consists of two parts. One is the recognition of the particles from a raw image by an image-processing technique in order to obtain the sizes and positions of the particles, and the other is a measurement technique of Particle Tracking Velocimetry based on fuzzy logic for the falling velocities of particles. The method is examined by a numerical experiment with computer-generated images. The result shows that the present method can be applied on-line for real-time processing of practical measurements.