bing hu and jiangang lu department of civil and environmental engineering

11Presented to Prof. Yu-Hen Hu as a Class Project for ECE533

Digital Processing Techniques for Digital Processing Techniques for Transmission Electron Microscope Transmission Electron Microscope

Images of Combustion-generated SootImages of Combustion-generated Soot

Bing Hu and Bing Hu and Jiangang Lu Jiangang Lu

Department of Civil and Environmental EngineeringDepartment of Civil and Environmental EngineeringUniversity of Wisconsin – MadisonUniversity of Wisconsin – Madison


Motivation and BackgroundMotivation and Background

Quantified characterization of flame-generated soot is Quantified characterization of flame-generated soot is critical for soot research.critical for soot research.

TEM-based study of soot properties is a reliable TEM-based study of soot properties is a reliable approach to quantifying soot size and morphology.approach to quantifying soot size and morphology.

Limited to the quality of TEM images, this approach Limited to the quality of TEM images, this approach may be facing challenges.may be facing challenges.


ObjectiveObjective

By applying extensive digital image processing By applying extensive digital image processing techniques to TEM images of soot particles, images techniques to TEM images of soot particles, images with high qualities in senses of machine detection with high qualities in senses of machine detection as well human visual inspection can be achieved.as well human visual inspection can be achieved.

Developed an accurate as well as efficient Developed an accurate as well as efficient computational analysis of soot size and morphology computational analysis of soot size and morphology based on automatic computer detection.based on automatic computer detection.


Typical TEM Images of SootTypical TEM Images of Soot Low contrast, noise Pseudo edges caused by electron diffraction


ApproachApproach

Enhance contrast by gray level transformation.

Reduce noise by low-pass filtering.

Eliminate pseudo bright edges by blurring filtering.

Segmentation of foreground from background by thresholding.

Compensate for imperfect thresholding by morphological processing.

Identify objects by morphology processing and segmentation.

Computational analysis based on pixel value.


Contrast EnhancementContrast Enhancement


Noise/fines detail RemovalNoise/fines detail Removal


ThresholdingThresholding Global Thresholding Adaptive Local Thresholding


Morphologic ProcessingMorphologic Processing


Object Extraction and MeasurementObject Extraction and Measurement

Identify objects through extracting connected components.

Measure maximum length.

Measure projected area.


Summary and ConclusionsSummary and Conclusions

An economical, accurate, and rapid image An economical, accurate, and rapid image processing and analysis approach has been processing and analysis approach has been developed for analyzing soot morphology developed for analyzing soot morphology information from the Transmission Electron information from the Transmission Electron Microscope images. Microscope images.

The techniques involved in this study include gray The techniques involved in this study include gray level transformation, convolution filtering, level transformation, convolution filtering, histogram analysis, thresholding, edge detection, histogram analysis, thresholding, edge detection, image opening, extraction of connected image opening, extraction of connected components, and computational pixel analysis. components, and computational pixel analysis.

bing hu and jiangang lu department of civil and environmental engineering

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