What Is Image Segmentation Annotation?
What Is LiDAR Annotation?
Image segmentation is a technique used to annotate images or videos by dividing them into regions based
on their visual properties, such as color, texture, or shape.
Image segmentation groups or labels similar regions on a pixel level, that is each pixel in the image is labelled with a corresponding class label.
In image segmentation, an image has two main components: “Things” and “Stuff”. Things refer to the countable objects in an image (like persons, cars, animals, etc.). Stuff refers to the uncountable regions in an image (like sky, ocean, grass, etc.).
Image segmentation groups or labels similar regions on a pixel level, that is each pixel in the image is labelled with a corresponding class label.
In image segmentation, an image has two main components: “Things” and “Stuff”. Things refer to the countable objects in an image (like persons, cars, animals, etc.). Stuff refers to the uncountable regions in an image (like sky, ocean, grass, etc.).
Types Of Segmentation
Types Of Segmentation
Semantic Segmentation
Semantic Segmentation
Semantic segmentation would assign unique class labels to each of these textures or categories. However, semantic segmentation's output will not differentiate or count the two cars or three pedestrians separately.
Instance Segmentation
Instance Segmentation
Panoptic Segmentation
Panoptic Segmentation
Panoptic Segmentation combines both semantic and instance. Here each pixel in a scene is assigned a semantic label as well as a unique instance identifier.
Panoptic segmentation assigns each pixel a semantic label as well as an instance identifier wherever applicable.
In the case of overlapping pixels, panoptic segmentation resolves the discrepancy by favoring the object instance, as the priority is to identify the thing rather than the stuff.
Image Segmentation Tools
Image Segmentation Tools
| Brush Tool | The main Image Segmentation tool is the Brush Tool, with adjustable brush stroke size. | |
| Polygon Tool | Polygon Tool is also widely used with a series of connected points or vertices. |
Use Cases
Use Cases
The Use Cases of Image Segmentation across the 3 types are the same as those of Polygon technique. The
difference being the Image Segmentation technique is more accurate as it is done at a pixel level.
Use cases include:
Use cases include:
| Object Recognition | Used in Autonomous Driving, Surveillance, and Robotics | |
| Medical Imaging | Used in Radiology, Surgery, and Pathology | |
| Augmented Reality | Used in the fields of Gaming, Advertising, and Ed-Tech | |
| Scene Understanding | Used in the fields of Robotics, and Urban Planning |
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