Image segmentation is an important task in computer vision and image processing, and has been widely used in various fields in recent years, including security systems, biometric systems, medical diagnostics, and other applications. Traditional image segmentation methods are popular among segmentation methods due to their ease of implementation, high processing speed, and the ability to work with a limited amount of data. In this work, the traditional methods of face image segmentation are researched, and each of these methods has its own characteristics, advantages and disadvantages. Also, information about machine learning methods used in segmentation and the results of their comparative analysis are presented.
| Mualliflar | Mamatov, N.S., Erejepov, K.K., Narzullayev , I.S., Jalelova, M.M. |
|---|---|
| Jurnal | Рақамли технологияларнинг назарий ва амалий масалалари |
| Nashr sanasi | 2024-04-09 |
| Jild | 7 |
| Son | 1 |
| Betlar | 24-30 |
| Til | Rus |
| DOI | 10.62132/ijdt.v7i1.157 |
DOI: 10.62132/ijdt.v7i1.157 · Maqolaning asl sahifasi
face image, thresholding, color space, classification, image processing, segmentation, biometrics, noise, support vectors, machine learning, yuz tasvir, bo‘sag‘a, rang maydoni, tasniflash, tasvirni qayta ishlash, segmentatsiya, biometrika, shovqin, tayanch vektorlar, mashinali o‘qitish
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