Facial Tracking, Recognition, and Utilizing Gaussian Blur In Face Recognition Sytems Via The OpenCv Library

Abstract

Face recognition technology attracts great attention in many technological areas. The development of face recognition algorithms has made significant contributions to the elimination of deficiencies in the field of image processing. Especially image processing libraries such as OpenCV provide a reliable and regularly updated platform for researchers and developers. OpenCv, which includes face recognition algorithms, is an image processing library that facilitates image processing. Some people may not want their faces to be seen in videos, movies or live broadcasts, and objectionable images and harmful products such as cigarettes and alcohol may need to be censored. In this case, the Gaussian filter comes to our rescue. The Gaussian filter is a filter widely used in image processing techniques and known for its blurring feature. The Gaussian filter is also called blurring in image processing software. The Python language is a programming language that can work independently of the platform. The Python language contains many libraries and is easy to program. The OpenCv library, like many other libraries, has generally been used with the Python language because it works very well with the Python language and is easily programmed. Many projects developed with Python language and OpenCv can be seen in academic sources. The aim of this study is to perform face recognition using OpenCV library and automatically apply Gaussian filter to recognized faces. All existing software does not automatically blur the desired faces. Doing this process manually is both time-consuming and jeopardizes the protection of privacy due to the unnoticed parts of the manual application process. Possible users of this project include televisions, production companies, broadcasters and YouTubers. This project can contribute to more effective protection of privacy and save time. This article can provide a method for researchers, industry experts and academics.

Keywords

• Face recognition
• OpenCv
• Gaussian filter
• image processing
• bluring

Facial Tracking, Recognition, And Utilizing Gaussian Blur In Face Recognition Sytems Via The OpenCv Library

Abstract

Face recognition technology attracts great attention in many technological areas. The development of face recognition algorithms has made significant contributions to the elimination of deficiencies in the field of image processing. Especially image processing libraries such as OpenCV provide a reliable and regularly updated platform for researchers and developers. OpenCv, which includes face recognition algorithms, is an image processing library that facilitates image processing. Some people may not want their faces to be seen in videos, movies or live broadcasts, and objectionable images and harmful products such as cigarettes and alcohol may need to be censored. In this case, the Gaussian filter comes to our rescue. The Gaussian filter is a filter widely used in image processing techniques and known for its blurring feature. The Gaussian filter is also called blurring in image processing software. The Python language is a programming language that can work independently of the platform. The Python language contains many libraries and is easy to program. The OpenCv library, like many other libraries, has generally been used with the Python language because it works very well with the Python language and is easily programmed. Many projects developed with Python language and OpenCv can be seen in academic sources. The aim of this study is to perform face recognition using OpenCV library and automatically apply Gaussian filter to recognized faces. All existing software does not automatically blur the desired faces. Doing this process manually is both time-consuming and jeopardizes the protection of privacy due to the unnoticed parts of the manual application process. Possible users of this project include televisions, production companies, broadcasters and YouTubers. This project can contribute to more effective protection of privacy and save time. This article can provide a method for researchers, industry experts and academics.

Keywords

• Face Recognition
• OpenCv
• Gaussian Filter
• Image Processing
• Bluring

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