How to Remove Background of an Image with Computer Vision

Removing the background from an image is a versatile technique widely used in computer vision projects for both creative and analytical purposes. Often employed in art and advertising to creatively manipulate images or isolate objects for further analysis, this technique generally involves identifying the foreground, creating a boundary around it, and making everything outside that boundary transparent, typically saving the result as a .png file. The post details a method for building a custom background removal application using Roboflow, a platform that provides a no-code interface for designing workflows. Two methods for background removal are introduced: one using YOLOv8 object detection to draw bounding boxes and another using YOLOv8 segmentation for more precise cropping, with the latter generally being more effective. Users can create and customize workflows without coding by selecting models that fit their needs, offering flexibility in speed and accuracy depending on the image size and project requirements. Background removal is particularly useful in preventing accidental detections in complex images and is applicable in various scenarios, such as isolating specific elements like hands in crowded photos for more accurate analysis.