2022
DOI: 10.35970/jinita.v4i1.1214
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Penerapan Metode Median Filtering untuk Optimasi Deteksi Wajah pada Foto Digital

Abstract: Deteksi wajah pada foto digital bertujuan untuk mendapatkan area wajah pada foto tersebut. Sering terjadi masalah saat mendeteksi wajah yakni terdapat banyak noise pada foto digital sehingga berpengaruh pada saat proses pendeteksian. Maka dari itu pada penelitian ini menerapkan metode median filtering untuk memperbaiki foto digital dengan mengurangi noise pada foto yang akan diuji. Keuntungan menggunakan filter ini adalah menjaga tepi agar tetap halus sekaligus mengurangi noise yang bertujuan untuk meningkatka… Show more

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Cited by 2 publications
(2 citation statements)
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“…The fastest time was obtained in the 21 st sample with a time of 0.66 seconds. Previous face detection studies used the median filtering method and got pretty good results [9] [10]. Meanwhile, based on the results obtained in this study, the Mean Filtering method works well to reduce noise caused by physical disturbances in the acquisition tool or intentionally due to improper processing.…”
Section: Resultsmentioning
confidence: 66%
“…The fastest time was obtained in the 21 st sample with a time of 0.66 seconds. Previous face detection studies used the median filtering method and got pretty good results [9] [10]. Meanwhile, based on the results obtained in this study, the Mean Filtering method works well to reduce noise caused by physical disturbances in the acquisition tool or intentionally due to improper processing.…”
Section: Resultsmentioning
confidence: 66%
“…By using the Median and Mean Filtering methods and evaluating their viability for usage in the situation of face detection in digital photographs, this study resolves the issue at hand. Research using the mean filtering method had previously been conducted with a total of 30 test samples [5] and research using the median filtering method had previously been conducted with a total of 10 test samples [6]; however, the two studies were conducted independently and used different numbers of samples. Because of this, the researchers used 30 sample photos to assess the two approaches' viability and determine which one worked best.…”
Section: Introductionmentioning
confidence: 99%