Computer-aided detection and morphological characterization of nanotube layers using scanning electron microscopy images

We propose an approach for computer-aided morphological analysis of titania nanotube arrays by using high-resolution scanning electron microscopy images. Based on top-view images and several preset parameters, our experimental MATLAB (R) routine finds possible candidates for nanotube openings and validates them by size, solidity, and eccentricity. Centers and inner diameters are computed followed by a local validation of pixels belonging to nanotube openings and walls. To achieve this goal, input gray level images are repeatedly converted to black and white using the entire range of thresholds from 254 to 1 to reveal black patches as nanotube openings. Nanotube locations are identified level after level in a systematic manner, taking into account the local gray level distribution. This approach allowed to identify most nanotubes in a reasonable computation time. When the nanotube detection is completed, the routine computes the nanotube surface density, the average nanotube diameter, the percentage of area occupied in the input image by nanotubes and unreacted titania, and the distribution of nanotubes based on their diameter, solidity and eccentricity. Our method provides a reliable and automated quality assessment of titania nanotube array layers used in sensor-based and photocatalytic applications. The total number of the detected nanotubes in the SEM images is dramatically increased by 30% to 40% when compared to previous methods. The proposed procedure can be easily adjusted for morphological analysis of any other materials structured as nanotube layers.