About this Abstract |
| Meeting |
MS&T25: Materials Science & Technology
|
| Symposium
|
Porous Materials for Energy and Environment Applications
|
| Presentation Title |
Automated pore identification and quantification using edge vectorization |
| Author(s) |
Michael Mulligan, Oliver Fowler, Josh Voell, Howie Fang, Mark Atwater |
| On-Site Speaker (Planned) |
Michael Mulligan |
| Abstract Scope |
The functional performance of micro- and nanoporous metals and alloys is dictated by the pore features such as size, connectivity, and morphology, and direct observation using scanning electron microscopy (SEM) often provides important details unavailable through other means. Hundreds or even thousands of pores may be present in each image, and efficient identification, classification, and quantification of pore characteristics require automated processing of the pixels for edge recognition, but the edges in these images are often not readily identified by popular image processing software, such as Image J. To address this, a software framework was designed and implemented in which vectorization was adopted as the key technique for edge detection using both the magnitude and directionality of the detected edges. This technique allowed for broken or incomplete edges to be recovered into complete pores, while filtering out noise. This greatly reduces analysis time while maintaining a high-level of accuracy. |