Pioneered a decade ago for remote sensing, eCognition enables geospatial data such as images, point clouds and GIS/CAD vectors to be integrated and analyzed to quantify features or detect changes over time. eCognition 9 simplifies and reduces the time taken to classify objects in data sets using deep learning, object based image analysis, and template matching functions. In addition, the lasted version adds also 3D point cloud analytics to the software so customers can perform a broader range of geospatial analysis with a greater level of control.
Version 9.4 includes user interface improvements that are designed to make rule set development quicker by making tools more efficient.
By leveraging deep learning technology from the Google TensorFlow™ library, eCognition empowers customers with highly sophisticated pattern recognition and correlation tools that automate the classification of objects of interest for faster and more accurate results. eCognition now provides new algorithms to directly leverage this state of the art machine learning technology. The new tools include a trainable convolutional neural network model and algorithms for the automatic generation of sample patches, train and apply model as well as the ability to save and load models into eCognition.
The new 3D point cloud capabilities in eCognition enable users to integrate aerial and terrestrial point cloud data to perform complex 3D data classification, extract information and analyze change over time. Available algorithms allow automated point cloud classification and transferring thematic information between point clouds. The latest eCognition version provides new point cloud viewing features to support 3D vector display together with the point cloud for a full spatial understanding of point cloud features.
eCognition extends the existing knowledge-based and supervised classification methods with computer vision based object detection. The Template Editor Window allows users to easily collect samples to define the search template that is applied over the imagery data. Additionally, a template matching algorithm is available to create a correlation coefficient layer used to detect objects.
New dialogs allows user to quickly populate and configure projects within eCognition Developer through simple drag and drop functions.The View Setting window and tools puts data visualization in a single, easy to access, location to better support data fusion for projects that combine image, vector and point cloud data. The Source View window provides a data management area to modify input layer alias, display orders and access information on file details.