Determining particle size distributions from video images by use of image processing

Recently a lot of research is being done on cohesive sediment. It plays a major role in the shoaling of harbours and waterways, and in some serious environmental problems. To predict cohesive sediment transport, information is needed about the distributions of size and settling velocities. Many methods exist to determine sizes suspended particles, but most are not applicable to cohesive sediment flocs, because of their fragility. If not at sampling, the flocs break at the subsequent analysis by for example the Coulter Counter or the pipet method. In case of analysis by the Owen tube another problem occurs next to the floc break up at sampling: the long duration of the analysis leads to additional flocculation and causes the measured distribution to be even more unrealistic. To solve these problems, exposures are made by underwater cameras, which give instantaneous information about the undisturbed samples. From one exposure the floc sizes can be determined, and from two successive exposure with known time between them, the settling velocities can be determined. 50 far, the analysis of exposures of flocs was mainly done by hand. Image processing by computer provides a way to do this automatically. It saves time, and consequently more flocs can be analyzed, leading to more representative distributions. The subject of th is report is the development and testing of an image processing program to determine the size distribution. The program is applied to digitized exposures, as can be made by a framegrabber. The framegrabber converts a recording on tape or from a ccd camera into a matrix of digits, the value of each digit representing the brightness of the corresponding pixel. From this grey value image, the image processing program has to distinguish the relevant objects, in other words, make a binary image, consisting of object pixels and non object pixels. This is quite complicated, due to inevitable interferences on the exposures like background features and shadow effects. After producing the binary image, the program has to determine partiele sizes and calculate and plot the size distributions. This report describes the problems that are met when segmenting objects from a background (chapter 2), the mathematica I methods to overcome them (chapter 3), some tests with the software that has been developed (chapter 4), and the results of these tests (chapter 5). The tests have been done on exposures with reference objects (ideal objects and background). The results are also visualized in the appendices. Also details on the software, that was developed using a software package for image processing, TCU, are given in the appendices