Euclidean Distance Filter for Image Processing

Hassanpour, Hamid

doi:10.36227/techrxiv.13664615.v1

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Euclidean Distance Calculation1

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2021

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“…After successfully detecting the face and different facial parts, the fourth step is to calculate the length and width of those regions. To calculate the length and width of those extracted facial features the Euclidean Distance [12] measurement formula shown in equation 3 is used.…”

Section: Euclidean Distance Calculationmentioning

confidence: 99%

Normal and Abnormal Human Face Detection Based on DCT and FFT Techniques - A Proposed Method

Bandyopadhyay¹,

Dutta²,

Goyal³

et al. 2021

Preprint

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In today’s world face detection is the most important task. Due to the chromosomes disorder sometimes a human face suffers from different abnormalities. For example, one eye is bigger than the other, cliff face, different chin-length, variation of nose length, length or width of lips are different, etc. For computer vision currently this is a challenging task to detect normal and abnormal face and facial parts from an input image. In this research paper a method is proposed that can detect normal or abnormal faces from a frontal input image. This method used Fast Fourier Transformation (FFT) and Discrete Cosine Transformation of frequency domain and spatial domain analysis to detect those faces.

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Section: Euclidean Distance Calculationmentioning

confidence: 99%