Image and video annotation can be difficult if we have a limited amount of tools. For example, you cannot use bounding box when the object is partially visible, or if the object is large. In both cases, the object of interest is either attached to the object of no interest. In such an instance, opt for something that is more sophisticated and agile (i.e., Polygon annotation tool).
This article sheds light on the Polygon annotation tools; its drawback, importance, and application. This article also presents five different tools and services that provide polygon annotation.
Let’s get started.
What is Polygon Annotation?
Polygon annotation is a process in which a set of points is used to define the boundaries of an object or region of interest in an image or video. These points are typically connected by lines to form a closed shape — a polygon. Those polygons surround the object or region in such a way that it takes the shape of the object. Polygon annotation is often used in the field of computer vision to provide training data for machine learning models.
One of the primary benefits of polygon annotation is that it allows for more precise and accurate labeling of objects or regions in images or videos. Rather than using a simple bounding box or circle to enclose an object — which may capture an object of least or no interest, polygon annotation creates more complex shapes that more accurately represent the boundaries of the object. This can be especially important when working with objects or regions that have irregular shapes or are partially occluded.
Where is Polygon annotation used?
Polygon annotation is often used in tasks such as object detection and image segmentation, where it is important to accurately identify the boundaries and features of objects or regions in the image. It may be used to annotate objects in images for object detection, or to define the boundaries of cells in microscopy images or even radiology for image segmentation.
Drawback of Polygon annotation
Polygon annotation can be a time-consuming and tedious process, as it requires manually labeling each point on the boundary of the object or region. To improve efficiency, it may be necessary to use specialized tools or software that create polygons with fewer points, or automatically create polygons based on user-defined rules.
Importance of Polygon annotation
Polygon annotation is of great importance as it is often necessary to provide the high-quality training data that is required to develop accurate machine learning models. They provide precision and agility to the training dataset.
How Does Polygon Annotation Work?
Polygon annotation is a process of drawing a series of connected straight lines on an image to enclose a specific area of interest. This is typically done using a graphical user interface (GUI) that allows the annotator to draw the lines with a mouse or stylus on a computer or tablet. The lines are then automatically connected to form the closed shape of a polygon.
After forming the polygon around the object, it is necessary to label the object with a descriptive tag. This label ensures the model understands what exists within the polygon annotation. Thus, polygon annotation provides a pixel-perfect labeling process for the irregular and complex datasets.
Polygon Annotation in Action: Use Cases
- Image segmentation. This is one of the most common use cases of polygon annotation. Here, an image is divided into different regions or segments. This is useful for tasks such as object recognition, image classification, and image processing.
- Object detection. Here, we identify the location and class of objects within an image. This is important for applications such as autonomous vehicles, security systems, and robotics.
- Medical image analysis. Radiology, being the eye of medicine, requires a tool that accurately captures anomalies in scans. Here, polygon annotation is used to identify and label different structures or abnormalities within an image or scan. This is helpful in applications such as cancer diagnosis, disease diagnosis, and surgical planning.
- Land use and land cover mapping. Polygon annotation is also helpful in identifying and labeling forests, grasslands, and urban areas. This is useful for a variety of applications, including environmental monitoring and resource management.
- Geographic Information Systems (GIS). Geologists use polygon annotation to create maps and spatial data for use in GIS applications such as environmental analysis, urban planning, and disaster management.
- Computer vision research. Polygon annotation is often used in computer vision research to provide the ground truth data needed to train and evaluate machine learning models.