## Identifying features

A hallmark of most CellProfiler pipelines is the identification of cellular features in your images, whether they are nuclei, organelles or something else.

A number of modules are dedicated to the purpose of detecting these features; the IdentifyPrimaryObjects module is the one that is most commonly used. The result of this module is a set of labeled objects; we define an object as a collection of connected pixels in an image which share the same label. The challenge here is to find a combination of settings that best identify the objects from the image, a task called segmentation. The typical expectation is to end up with one object for each cellular feature of interest (for example, each nucleus is assigned to a single object in a DNA stained image). If this is not the case, the module settings can be adjusted to make it so (or as close as possible). In some cases, image processing modules must be used beforehand to transform the image so it is more amenable to object detection.

In brief, the workflow of finding objects using this module is to do the following:

- Distinguish the foreground from background: The foreground is defined as that part of the image which contains the features of interest, as opposed to the background which does not. The module assumes that the foreground is brighter than the background, which is the case for fluorescence images; for other types of images, other modules can be used to first invert the image, turning dark regions into bright regions and vice versa.
- Identify the objects in each foreground region: Each foreground region may contain multiple objects of interest (for example, touching nuclei in a DNA stained image). Recognizing the presence of these objects is the objective of this step.
- Splitting clusters of objects: If objects are touching each other, the final step is to separate them in a way that reflects the actual boundaries as much as possible. This process is referred to as "declumping."

The module also contains additional settings for filtering the results of this process on the basis of size, location, etc. to get the final object set. At this point, the objects are ready for measurements to be made, or for further manipulations as a means of extracting other features.

Other modules are able to take the results of this module and use them in combination with additional images (like IdentifySecondaryObjects) or other objects (like IdentifyTertiaryObjects) to define yet more objects.

For more information on these identification modules work and how to configure them for best performance, please see the detailed help by selecting the IdentifyPrimaryObjects module and clicking the button at the bottom of the pipeline panel.

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