Workflow translation and dynamic invocation for Image Processing based on OpenCV

Human Computer Interaction (HCI) can be improved drastically using the hand gesture based recognition system. This system is designed to detect the gestures of the hands in the images captured in real time. There are certain areas of intersect in the hands that are there for the classification. The gaming devices like Xbox, PS4 and smart phones are also using this method to solve few problems. In this paper a smart method i9s developed to solve the problem. Using Python 3.9 and MediaPipe, the hand gestures are recognised in the real-time images. The background subtraction is the key method used to generate the results. The hand is detected and processed for the finding of the binary image with the fixed number of pixels. The palm position, dimension and the gesture are recognised. In this experiment, the finger count and the position of the fingers is considered as the gesture. The finger count can also be calculated after the hand is recognised. The major areas of the Image Processing and the MediaPipe in Python are covered to solve this problem.

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Workflow translation and dynamic invocation for Image Processing based on OpenCV

Cited by 3 publications

References 3 publications

Image Processing Using OpenCV Technique for Real World Data

Image Processing Using OpenCV Technique for Real World Data

Motion Detection and Alert System

MediaPipe to Recognise the Hand Gestures

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