Colour Detection and Segmentation based Invisible Cloak
Description
This research paper presents a fascinating project on creating an "Invisible Cloak" effect using Python and Computer Vision techniques. While true invisibility is still a fantasy, our approach leverages Color Detection and Segmentation to achieve a captivating visual illusion. The system identifies the person wearing the cloak and the background colors, then seamlessly blends the person with the surroundings, giving the appearance of vanishing from view. We explore the potential applications in entertainment, augmented reality, and creative visual effects. The methodology is straightforward, utilizing existing computer vision techniques, making it accessible and capable of real-time processing. However, challenges exist, such as sensitivity to lighting and background complexities. This project aims to creates a magical experience by using an Image Processing technique called Color Detection & Segmentation resulting in false sense of Invisibility in the frame. OBJECTIVES: 1- Capture & Store background frame using Image Acquisition by Store a single frame before starting the infinite loop 2- Detect the defined color using color detection & segmentation algorithm 3- Segment out the defined colored part by generating mask & applying it on frame 4- Generate the final output to create a magical effect by combining frames together, & remove the unnecessary noise from masks.
Files
Steps to reproduce
Requirements: -Python (3.x recommended) -Python Imaging Library (PIL) or Pillow (for image manipulation) Steps: Capture Background Image: Set up a camera or use an existing photo of the background without the subject (the person wearing the "cloak"). This will serve as the background for the illusion. Capture Subject Image: Capture a photo of the subject wearing a green or blue garment. The choice of color depends on what color will stand out the least against the background. Green or blue is commonly used in film and photography for chroma key (green/blue screen) effects. Image Segmentation: Use image processing libraries like OpenCV or Pillow to segment the subject from the background. The goal is to create a mask where the subject is highlighted in one color and the background is in another. Replace Background: Replace the background of the segmented subject with the previously captured background image. This will create the illusion of the subject being "invisible" against the new background. Adjust and Refine: Fine-tune the mask and color adjustments to ensure a convincing effect. This may involve adjusting colors, transparency, and blending to make the subject seamlessly blend into the new background. Display the Result: Display the final composite image, which gives the illusion of invisibility against the new background.