Understanding Jaccard’s Index and Dice Coefficient in Object Detection and Image Segmentation

Object detection and image segmentation are essential tasks in computer vision, involving the identification and localization of objects within images. To evaluate the accuracy of these techniques, metrics like Jaccard’s Index and Dice Coefficient are used. Jaccard’s Index measures the degree of overlap between bounding boxes or masks, while Dice Coefficient quantifies the similarity between two masks. This article delves into the concepts and applications of these evaluation metrics.

In object detection, there are two distinct tasks:

• Determining whether an object exists in the image (classification)
• Fetching the location of the object (localization, a regression task).

In an image segmentation task, we also fetch the shape of the objects instead of just the bounding boxes around them.

Also, in a typical data set there are many classes, and their distribution is…