IPSDK Explorer Artificial Intelligence modules for Segmentation

In addition to traditional image analysis and processing solutions, IPSDK also provides artificial intelligence (AI) solutions.

IPSDK offers two innovative and revolutionary modules based on Machine Learning techniques: Smart Segmentation and Smart Classification. Although technologically highly advanced, these new tools have been designed to be easily used by all IPSDK users, even novices.

Moreover, IPSDK offers the possibility of generating learning models in the IPSDK Explorer graphical interface, using easy-to-use interactive tools. These models can then be used in the interface or in scripts to rapidly process large quantities of images.

 

Machine Learning Segmentation : Sum up

– Innovative, revolutionary learning tool

– Fast and user-friendly

– Immediate visualization of learning results

– Can be used in 2D and 3D

– Smart Segmentation: pixel classification

– SuperPixel Segmentation: classification of blocks of pixels automatically pre-cut into homogeneous zones 

–  Random Forest Algorithms

– Customizable model descriptors

Smart Segmentation : Pixel classification

Smart Segmentation is used to automatically classify pixels or voxels in an image.

After a quick, user-friendly manual segmentation learning stage, the Machine Learning tool quickly and automatically defines the rules for classifying image pixels.

This training is used by the Machine Learning algorithm to generate a model that can then be used to automatically classify the entire image. This model can then be used to segment other similar images.

⇒ How to use the Smart Segmentation module in IPSDK Explorer?

Introduction to the SMART Segmentation module available in the IPSDK software.

This video shows how to build a model using the interactive learning tool to automatically and simply classify pixels in an image.

The algorithm, based on Random Forest techniques, identifies the discriminant measures to be used to classify objects according to the training proposed by the user.

Super pixel/Voxel Segmentation : Classification of blocks of pixels automatically pre-cut into homogeneous zones

As an alternative to Smart Segmentation, IPSDK Explorer offers Super Pixel Segmentation for processing thicker objects. This second module automatically classifies pixels or voxels in an image, based on a pre-cut into homogeneous zones.

This tool begins by grouping together zones of homogeneous pixels. The next step is to associate a few of these super-pixels with each class. This training is used by the Machine Learning algorithm to generate a model that can then be used to automatically classify the entire image. This model can then be used to segment other similar images.

Super Pixel smart segmentation enables objects to be outlined quickly and efficiently.

⇒ How to use the Super-Pixel Segmentation module in IPSDK Explorer?

Presentation of the Super-Pixel segmentation module available in IPSDK software from version 3.2.

This video shows how to generate a regular image split by adjusting the super-pixel border to the edges of objects. This allows pixels to be grouped into homogeneous zones.

The video then shows how to build a model using the interactive learning tool to classify super-pixels automatically and simply.

The algorithm, based on Random Forest techniques, identifies the discriminating measures to be used to classify them, according to the training proposed by the user.