1 / 15

Standardized Micro-Scale Mixing Evaluation

Standardized Micro-Scale Mixing Evaluation. Guillermo González-Fernández Benjamin Yang. Outline. Introduction and Motivation Project Goal and Success Measure Raw Images Image enhancement Edge detection Evaluation Results Custom area mixing evaluation. Introduction and Motivation.

gualtier
Download Presentation

Standardized Micro-Scale Mixing Evaluation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Standardized Micro-Scale Mixing Evaluation Guillermo González-Fernández Benjamin Yang

  2. Outline • Introduction and Motivation • Project Goal and Success Measure • Raw Images • Image enhancement • Edge detection • Evaluation • Results • Custom area mixing evaluation

  3. Introduction and Motivation • Micro scale mixing crucial to success of many fields • No standardized comparison • Characteristics in microfluidics • Low Reynolds number • Laminar Flow • Diffusion Limited Image: A.D. Strook et al., “Chaotic Mixer for Microchannels,” Science, vol 295, pp. 647-651, 2002

  4. Project Goal and Success Measure • Evaluate the extent of mixing in standardized experimental images • Success will be based on correlation to existing simulation results Standard Y-channel Square-wave channel Compartment channel

  5. Raw Images A B E F G C D

  6. Image enhancement (I) • Why image enhancement? Better edge detection • Study the images: histogram, 2D-DFT… • Apply Matlab filters • Design new filters: • Gaussian • Sobel • Prewitt • Laplacian • Log • Unsharp • Min, med, max • Contraharmonic • New gaussian filter (gaussian iterations)

  7. Image enhancement (II) Min Max Med Contraharmonic Gaussian iterations

  8. Image enhancement (III) • Cascade different combinations of the filters • Final image obtained by averaging best results : • Average-gaussian-average • Average-gaussian-gaussian • Average-gaussian iterations-gaussian • Average-gaussian iterations-average

  9. Edge detection • We don’t know the real edge!! • Matlab edge detection strategies • New strategies • Y channel: Perfect boundary • Square channel: General method

  10. Edge detection • We don’t know the real edge!! • Matlab edge detection strategies • New strategies • Y channel: Perfect boundary • Square channel: General method

  11. Evaluation • Extract part of the image we will evaluate • Estimate mixing percentage

  12. Results

  13. Custom area mixing evaluation • User defines the image to evaluate • User defines area (rectangle) to evaluate • Obtain mixing efficiency

  14. References • [1] Bertsch, S. Heimgartner, P. Cousseau, and P. Renoud. “Static micromixers based on large-scale industrial mixer geometry”, Lab on a Chip, Vol 1, pp 56-60, 2001. • [2] A.D. Strook et al., “Chaotic Mixer for Microchannels,” Science, vol 295, pp. 647-651, 2002 • [3] R. H. Liu, M. A. Stremler, K. V. Sharp, M. G. Olsen, J. G. Santiago, R. J. Adrian, H Aref, and D. J. Beebe. "Passive mixing in a three-dimensional serpentine microchannel", J. of MEMS, Vol 9, No. 2, pp 190-196, 2000. • [4] V. Mengeaud, J. Josserand, and H. H. Girault. “Mixing processes in a zigzag microchannel: finite element simulations and optical study”, Analytical Chemistry, Vol 74, pp 4279-4286, 2002. • [5] R. Gonzalez, R. Woods. Digital Image Processing, 2nd Edition. Prentice Hall, Upper Saddle River, N.J, 2002. • [6] Kai Kang, R. Chevray. “Visualization of fluid mixing in microchannels”, IEEE Computer Graphics and Applications, Vol 25, Issue 6, pp 16-20, 2005. • [7] Leming Shi, Weida Tong, Zhenqiang Su, et al. “Microarry scanner calibration curves: characteristics and implications”, BMC Bioinformatics, Vol 6, pp. 1-14, 2005 • [8] Peter A. C. ‘t Hoen, Rolf Turk, Judith M. Boer, et al. “Intensity-based analysis of two color microarrays”, Nucleic Acids Research, Vol 32, No 4, pp. e41-e47, 2004

  15. Questions?

More Related