Color Detection & Segmentation based Invisible Cloak

Published: 29 August 2023| Version 1 | DOI: 10.17632/dpr2x6kjj3.1


This project is actually inspire from the cloak which is used in Harry Potter Movie. As in movie when harry put this cloak on itself it become invisible same as it in this program when a person put the cloak he/she will become invisible. We will create the Invisible Cloak using an Image Processing Techniques called Color Detection and Segmentation. AIM: The aim of the Invisibility Cloak Project using Image Processing is to develop a system that can digitally create the illusion of invisibility on a person in real-time camera. 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.


Steps to reproduce

1. Capture and store the background frame: The main concept is interchanging the current frame picture element equivalent to the fabric with the backdrop pixels, so that we obtain the magical effect of invisibility. Thus, we’re required to save a frame of the backdrop. 2. Identify the cloth (cloak) by using the Colour detection & segmentation algorithm: The correct concept is to change the color space of the picture from ‘R.G.B.’ (Red, Green, Blue) value to ‘H.S.V’ (Hue, Saturation, Value). About ‘H.S.V’ color space, ‘Hue’: It gives the information about color. ‘Saturation’: It explains about the intensity of the color. ‘Value’: It tells about the luminosity of color. Shading component of an pictures appears here. 3. Segmenting out the cloak by generating a mask: We refine the mask & then it is further used for segmenting out the fabric from the frame. 4. Generate the final augmented(magical) output to create Invisibility cloak: Finally, we’ll be replacing ‘the pixels value of the detected cloak colored area of the cloth with corresponding pixel value of the background’ & ultimately generating an augmented (magical) output. HSV stands for Hue, Saturation, and Value. It is a color space that represents colors in terms of: Hue: It is the color itself, and it is measured in degrees, the color portion of the model, expressed as a number from 0 to 360 degrees: Red falls between 0 and 60 degrees. Yellow falls between 61 and 120 degrees. Green falls between 121 and 180 degrees. Blue falls between 241 and 300 degrees. Magenta falls between 301 and 360 degrees. Saturation: It describes the amount of gray in a particular color, from 0 to 255. Reducing this component toward zero introduces more gray and produces a faded effect. Sometimes, saturation appears as a range from 0 to 255, where 0 is gray, and 255 is a primary color. Value (or Brightness): Value works in conjunction with saturation and describes the brightness or intensity of the color, from 0 to 255 , where 0 is completely black, and 255 is the brightest and reveals the most color.


Veer Bahadur Singh Purvanchal University


Computer Vision, Image Processing