Enhancing SPM and SEM Particle Size Analysis – The Improved SPIP 6.7

SPIPTM^TM version 6.7 enables easy and robust particle analysis in SEM and SPM images, thanks to the new and enhanced detection and splitting options.

Circle Detection

Using the new Circle Detection method, SPIPTM 6.7^TM can determine circular image features even when the contrast is weak, the image is noisy, and when the particles are overlapping or connected.

This allows particle counting or particle size distributions to be performed on images in which the common segmentation techniques will be unsuccessful.

Top: Microspheres. Bottom: Fiber glass composite. Courtesy of Force Technology

Automatic Particle Splitting

If particles get dispersed on a substrate, they may tend to agglomerate in small clusters of two or more adjoining particles. Every individual particle cluster will usually be identified as a single feature. SPIPTM 6.7^TM provides two automatic splitting options to compensate for this, i.e., they can split the clusters into individual particles.

STM image of MoS2 nanoclusters on a gold Au(111) substrate. Courtesy of iNano, University of Århus.

Manual Particle Splitting

The particle cutting tool has been enhanced with a magic splitting tool to facilitate manual splitting of particles. One or more shape(s) is selected, and the button is clicked to separate the shapes.

Particle splitting using the new magic splitting tool: Just select one or more shapes and click the tool

Improved Watershed Detection Algorithms

For a more robust detection in noisy images, the multi-scale watershed detection techniques have been substantially enhanced including automatic merging of neighboring shallow features in order to conform to ISO 25178-2.

With the improved watershed particle detection methods, it is now an easy task to, for example, detect particles on stepped surfaces. Image courtesy of Yun Liu, Dalian Institute of Chemical Physics.

New Parameters

The Particle & Pore Analysis function is usually employed for determining and measuring other shapes than pores or particles, for example lines on substrates or the layers in sandwich structures.

The width of a shape along its length direction for such features is described by a new set of “breadth” parameters. The local breadth is measured across the shape and from this, the maximum, minimum, standard deviation, and mean can be obtained. Therefore, all these parameters are reported for a line structure.

Other than reporting the projected area for particles, the “true 3D area” of particles found on height images can also be obtained by SPIPTM 6.7^TM. The area is a critical parameter for adsorbent materials and catalysts.

Automatic Outlier Masking in Plane Correction

In order to achieve excellent plane correction results, outliers are masked by thresholding them with the color scale clip markers. In doing this, the Z range used for estimation can be controlled.

However, to date, there is no straight forward method for achieving the same results in a batch processing context, because user interaction is required in this procedure. The plane correction settings can be saved with pre-adjusted color clip marker positions to achieve effortless outlier rejection in batch processing.

Additionally, a robust automatic outlier masking option has been included. As soon as the new masking option is enabled, SPIPTM^TM automatically masks features that stick out from the background as an integral part of plane correction.

By using SPIPTM 6.7^TM, excellent plane correction results can be easily achieved, especially with line-wise leveling. The line-wise leveling is often used in SPM for removing line-wise distortions.

Original image of a nano-indentation mark

Line-wise leveling without any masking

Line-wise leveling with automatic outlier masking.

Easy Scaling of SEM and TEM Images

In addition to the reading of the XY scaling information when available in EM images, including the .dm3 format, the tool for scaling SEM images is faster and easier to use.

The tool pops up in a temporary dialog in SPIPTM 6.7^TM, and supports automatic cropping to remove the information bar that is usually present in SEM images. Previously-defined settings can be employed to directly apply scaling and cropping from the ribbon, facilitating easy analysis of the EM images.

The new XY Scaling Dialog featuring automatic cropping. The scaling bar is typically identified automatically making it easy to set the XY-scaling factor.

Saved settings can be applied by the two-click QuickLaunch button.

Texture Analysis for SEM Images

A "texture analysis" feature has been added to the roughness analysis module. Accordingly, a subset of charts and statistical parameters can be calculated for non-topographic images, such as SPM image channels or SEM images which do not describe height.

Texture analysis includes, for example, first-order statistics parameters, mean, max, and min as well as advanced parameters such as texture direction, correlation length, a cross hatch angle, and more.

Texture analysis of an optical micrograph of a cross ground surface.

Visual Improvements

• SEM images and photographic images are by default displayed in grayscale
• As an option, color scale labels are adjustable in size and displayed next to the color scale itself. This is suitable for presentation and publication
• A brightness/contrast function has been included for easy adjustment of brightness and contrast if the color scale is not displayed. For example, for SEM users who may not want to view the color scale
• Images can be displayed with no color scale, but maintaining the XY axes

Labels inside (default)

Labels outside

No labels

No color scale

Other Powerful Tools and Improvements

• Morphology filters - Configurable dilation, erosion, opening, and closing grayscale morphology filters have been included. These are especially useful for preprocessing complex images prior to particle and pore analysis
• Measure Shapes (e.g. detected particles) can be imported and exported. For instance, to save the result of an excellent detection for processing e.g. in MATLAB, or for quickly applying a handful of manually created Measure Shapes
• Histogram analysis has a "binarize" function to enable easy thresholding of image. For instance, for use with particle analysis in situations where users want complete control over each segmentation step

Detected particles, “shapes”, can now be exported and for example be processed in MATLAB. Processed shapes can even be imported back into SPIPTM.

Help and Support

Free Support and Software Updates

Experienced Customer Service and Technical Support teamof Image Metrology can answer any queries and requests. Moreover, local assistance is always nearby thanks to a worldwide network of knowledgeable distributors.

All SPIPTM^TM licenses include one year of free support and software updates, which can be extended based on the customer’s wishes.

Additionally, the software includes an online help function, which has a range of video tutorials.

Welcome screen with examples

Comprehensive Help function

Online video tutorials

University and Network Installation

If there are a large number of users in the same group, SPIPTM^TM user groups can achieve a customized solution for their company or university.

Image Metrology can be contacted to learn more about an optimal solution for an institution or company.

This information has been sourced, reviewed and adapted from materials provided by Image Metrology A/S

For more information on this source, please visit Image Metrology A/S