--> For enrollment, data and more information on this course, please visit Learn.Trimble.com. You will have to create an account (for free) and enroll to this course.

In this "From The Ground Up" Session, we will have a look at Image Object Level hierarchies in the Trimble eCognition Developer software. 

Image Object Level (IOL) hierarchies is a data structure that incorporates image analysis results, which have been extracted from a scene. An image object is a group of pixels in a map. Each object represents a definite space within a scene and objects can provide information about this space. The first image objects are typically produced by an initial segmentation.

Within a project you can create multiple Image Object Levels, creating an Image Object Level hierarchy. Every image object is networked in a manner that each image object knows its context – who its neighbors are, which levels and objects (super-objects) are above it and which are below it (sub-objects). No image object may have more than one super-object, but it can have multiple sub-objects.

We will use this concept for extracting impervious surfaces on a sub-level and use this information to classify image objects on a super-level representing parcels.

The data set used in this course will be provided for download after enrollment. This course is free of charge. You will receive an certificate after completion of this course!


The training material was created with the eCognition Developer v10.1.1.

Please, if needed, download the free Trial version here.


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