# Recognize Objects

Distinguishing different objects under various viewing angles and lighting conditions is a common, yet difficult task. Approaches like pattern matching or color histogram comparison may be viable in certain cases. In general, however, they do not work reliably, are difficult to tune, and need to be carefully selected on a case-by-case basis by a vision expert.

In this tutorial, we will use the Green Classify Tool and its simple and intuitive interface to work on an image classification database containing 150 different objects. There are 24 images from different viewing angles for each object. The goal is to use a subset of images from each class to train, and then to test the resulting performance on the remaining, untrained images.

###### Learning Objectives

- Get to know the Green Classify tool.
- Tag images according to their class (use automatic tagging based on the image file names).
- Use a splitting ratio to separate training and testing samples to assess classification performance.
- Investigate the relevance of color for this application.