Face segmentation based on level set and improved DBM prior shape

Wu, Xiaoling; Zhao, Ji; Wang, Huibin

doi:10.1007/s13748-018-00169-5

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…Belgilarga asoslangan usullar yuz tasvirini segmentatsiyalash sohasidagi algoritmlar muhim sinfini ifodalaydi [19]. Bu usullarda tasvirdagi yuz chegaralarini aniqlash va raqamli tasvirlardagi fondan farqlash uchun tekstura, shakl va kontur kabi turli xil yuz belgilaridan foydalaniladi [20]. Ushbu usullar algoritmini quyidagicha tavsiflash mumkin:…”

Section: Yuz Tasvirini Segmentatsiyalashda Belgiga Asoslangan Usullarunclassified

Yuz tasvirlarini segmentlashning an’anaviy va mashinali oʻqitish usullari

Mamatov,

Erejepov,

Narzullayev

et al. 2024

Международный журнал теоретических и прикладных вопросов цифров

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Tasvirlarni segmentlash kompyuterli ko‘rish va tasvirlarni qayta ishlash sohasida muhim vazifa bo‘lib, so‘nggi yillarda turli sohalarda, shu jumladan xavfsizlik tizimlari, biometrik tizimlar, tibbiy diagnostika va boshqa ilovalarda keng qo‘llanilib kelinmoqda. Tasvirlarni segmentlashning an’anaviy usullari amalga oshirish qulayligi, yuqori ishlov berish tezligi va cheklangan miqdordagi ma’lumotlar bilan ishlash qobiliyati sabab segmentlash usullari orasida mashhurdir. Mazkur ishda yuz tasvirlarini segmentlashning an’anaviy usullari tadqiq qilingan bo‘lib, ushbu usullarni har birini o‘ziga xos xususiyatlari, yutuq va kamchiliklari bayon etilgan. Shuningdek, segmentlashda qo‘llaniladigan mashinali o‘qitish usullari haqida ma’lumotlar va ularni qiyosiy tahlil natijalari keltirilgan.

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Section: Yuz Tasvirini Segmentatsiyalashda Belgiga Asoslangan Usullarunclassified

Yuz tasvirlarini segmentlashning an’anaviy va mashinali oʻqitish usullari

Mamatov,

Erejepov,

Narzullayev

et al. 2024

Международный журнал теоретических и прикладных вопросов цифров

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“…With the rapid development of biometric recognition technology, face recognition [1] has been widely used in many fields. As the basic research of face recognition, facial image segmentation [2][3][4] is an important step in a face recognition system. Accurate and fast segmentation of the face is critical to improve the speed and accuracy of recognition.…”

Section: Introductionmentioning

confidence: 99%

Facial Image Segmentation Based on Gabor Filter

Fan

Zhang

et al. 2021

Mathematical Problems in Engineering

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As an important part of face recognition, facial image segmentation has become a focus of human feature detection. In this paper, the AdaBoost algorithm and the Gabor texture analysis algorithm are used to segment an image containing multiple faces, which effectively reduces the false detection rate of facial image segmentation. In facial image segmentation, the image containing face information is first analyzed for texture using the Gabor algorithm, and appropriate thresholds are set with different thresholds of skin-like areas, where skin-like areas in the image’s background information are removed. Then, the AdaBoost algorithm is used to detect face regions, and finally, the detected face regions are segmented. Experiments show that this method can quickly and accurately segment faces in an image and effectively reduce the rate of missed and false detections.

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Face segmentation based on level set and improved DBM prior shape

Cited by 2 publications

References 28 publications

Yuz tasvirlarini segmentlashning an’anaviy va mashinali oʻqitish usullari

Yuz tasvirlarini segmentlashning an’anaviy va mashinali oʻqitish usullari

Facial Image Segmentation Based on Gabor Filter

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