Different Biometrical Features for Detecting Human Intrusion Using Artificial Intelligence: Literature Review

Younis, Ansam

doi:10.33899/csmj.2022.176596

Cited by 1 publication

(1 citation statement)

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“…Two basic measures were used to determine the results: Right detection rate (RDR) [30], [31] and wrong detection rate (WDR) [30], [32], The results are calculated on the first scale by calculating the number of frames in which the face has been successfully identified to the number of total frames. The higher the value of this measure, the better the method of identifying the face in the frame would be.…”

Section: Resultsmentioning

confidence: 99%

Developing Viola Jones' algorithm for detecting and tracking a human face in video file

Younis

Ramo

2023

IJ-AI

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Face detecting and tracking in video clips is very important in many areas of daily life. All institutions, public departments, streets, and large stores use cameras from a security point of view, and detecting and tracking human faces is necessary for indexing and preserving information concerning the visual media. This paper presents a novel method for hybridizing the Viola_Jones face detection algorithm to track and identify a human face in video sequences. The method represents a combination of Viola Jones' algorithm with a measured normalized cross-correlation (NCC) algorithm with a template matching method using the Manhattan distance measure equation in the video between successive sequences After that, the fuzzy logic method is added in comparing the image of the face to be detected with the images of templates taken in the proposed algorithm, which increased the accuracy of the results, which reached 99.3%.

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