This paper describes a new method to measure the sizes of particles an
d their probability distribution function by image processing. In the
present research, an image with heavily overlapped particles was proce
ssed. The edges of the particles in the image are detected by Canny's
method, and the contours are linked from the pixels in the edges by us
ing chain-coding. The contours are subsequently segmented according to
the curvature. Constant curvature segments are clustered according to
some relations among contour segments which are likely to represent t
he same circle. The Least Squares Method which provides an accurate pa
rameter estimation is performed to find out the parameters of a circle
. The present method can recover most of particles even in a heavily o
verlapped particle image; It provides a useful way of investigating th
e structure of material or counting particles in many fields of engine
ering. Another advantage of the present method is its short computatio
nal time. All the computations in this paper were carried out on a per
sonal computer, and the computational rime of processing one image was
between 4-10sec on the personal computer (Pentium II, 300 MHz), which
depended on the number of particles in the image. It is clear that th
e present research can be extended to the real-time processing of part
icle-detecting and particle-measuring in the future.