Detection and volume estimation of semiconductor quantum dots from atomic force microscope images

Abstract

An automated quantum dot detection and volume estimation method of atomic force microscope images are proposed and implemented. Quantum dot detection is based on the image-segmentation method widely used in image processing. We used a modified local watershed algorithm, which produces stable and effective segmentation results in order to detect the peak position of the quantum dot of the atomic force microscopy image. An effective volume estimation of the quantum dot is performed by intelligently determining the boundary of the quantum dot at each height step and by simply adding small volume fractions lying inside of the quantum dot boundary. Our volume estimation results are quantitatively analyzed by comparison with the quantum dot volume obtained by assuming conical and pyramidal shapes. The detection results of our method are quantitatively compared with the results of two other methods for general grain detection, and with a transmission electron micrograph of the quantum dot. Finally, information such as the number of quantum dots, the density, the size and the height distribution are also provided as a result of implementing our method. This method can be applied to detect and estimate volume of a similar shape with a different size. (C) 2003 American Institute of Physics.