Application of a segmentation algorithm to quantum dots study
Paolo Belardinelli, S. Capoleoni, Brunello Tirozzi, Carlo Coluzza · Journal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena · 2004
A variation of the neural algorithm locally excitatory globally inhibitory network has been developed for automatic recognition, count, and morphological analysis of a large number of quantum dots. In a typical image of 256×256 pixels (500×500 nm2), the program recognizes the dots with an average error of about 3%. It also calculates area and height of each of them. Furthermore, the recognition procedure is very fast (less than 2–3 s on a Pentium III at 600 MHz).