Bearing Health Assessment Based on Different Types of Masses Voting Match and Mahalanobis Distance under Different Operating Conditions

Wang, Yihan; Nie, Guojian; Hu, Ning; Chen, Bingquan

doi:10.1145/3421766.3421870

Cited by 2 publications

(1 citation statement)

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“…This distance is defined as the distance between two points involving a multiplier and can reduce distance distortion caused by linear combinations, as shown in (21) [26]. The Mahalanobis distance (MD)based score is calculated as the minimum squared MD as shown in (21) [27].…”

Section: Mahalanobis Distancementioning

confidence: 99%

Facial recognition using multi edge detection and distance measure

Intan

Nurdin

Pangerang

2023

IJ-AI

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Face recognition provides broad access to several public devices, so it is essential in the midst of today's technology boom. Human face recognizing has challenge in using uncomplicated and straightforward algorithms quickly, using memory specifications are not too high, otherwise the results are quality and accurate. Face recognition using combination edge detection and Canberra distance can be recommended for applications that require fast and precise access. The application of several edge detections singly has low performance, so it requires a combination technique to obtain better results. The proposed method combined several edge detections such are Robert, Prewitt, Sobel, and Canny to recognize a face image by identification and verification. As a feature extractor, the combination edge detection forms a more robust and more specific facial pattern on the contour lines. The results show that the combination accuracy outperforms other extractor features significantly. Canberra distance produces the best performance compared to Euclidean distance and Mahalanobis distance.

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