Date recorded: February 20 2014

Duration: 01 hours 03 minutes 43 seconds

In this webinar, the first in a series of Masterclass presentations, we introduce the basic concepts of image analysis. We will discuss the parameters that can be measured and how we can relate this information to real world problems. The shape of a particle may affect a number of properties such as particle flow, packing density or reaction rates in a process or product. Therefore to fully understand your particles, and in turn your products, characterizing the particle shape may be beneficial.
Table of contents
1. Imaging masterclass 1Basic principles of particle characterization by automated image analysis
01:02
2. Overview
01:04
3. What is automated particle imaging?
00:06
4. Evolution of particle characterization
00:50
5. What is automated particle imaging?
00:29
6. What is automated particle imaging?
00:24
7. What is automated particle imaging?
00:54
8. What is automated particle imaging?
00:31
9. Why is particle imaging important?
00:10
10. Why is particle imaging important?
00:59
11. Why is particle imaging important?
00:55
12. Why is particle imaging important?
01:20
13. Basics principles of automated particle imaging
00:06
14. Basics principles of automated particle imaging
00:34
15. Basics principles of automated particle imaging
00:56
16. Sample preparation
01:28
17. Basics principles of automated particle imaging
00:30
18. Basics principles of automated particle imaging
00:06
19. Sample presentation
00:35
20. Static analysis
01:30
21. Sample presentation
00:45
22. Image capture and analysis
00:11
23. Image capture and analysis
01:29
24. Morphological shape descriptors
00:55
25. Morphological shape descriptors: elongation
00:35
26. Morphological shape descriptors: elongation
01:14
27. Morphological shape descriptors: convexity
01:22
28. Morphological shape descriptors: convexity
00:47
29. Morphological shape descriptors: circularity
00:21
30. Morphological shape descriptors: circularity
00:47
31. The third dimension - gives extra information
00:49
32. The third dimension
00:58
33. Data analysis
00:05
34. Number – volume relationship
00:33
35. Number distribution
01:12
36. Volume distribution
00:30
37. Number – volume conversion
00:32
38. Number based distribution : monitoring fines in recycling abrasive material
01:02
39. Minimum number of pixels
01:14
40. Scattergram - relate two parameters
01:24
41. Scattergram - relate two parameters
00:42
42. Scattergram - relate two parameters
00:30
43. Scattergram - relate two parameters
01:24
44. Scattergram - relate two parameters
00:08
45. Statistical analysis tool to compare large data sets
02:35
46. Summary: masterclass 1: basic principles of imaging
27:10