CAJ | 학술논문

为了更快地将肤色区域从图像中分割出来，在二维Ostu方法的基础上，提出了一种将积分图和粒子群优化相结合用于寻找最优分割阈值点的新方法。该方法通过对经过颜色补偿后的图片在YCbCr颜色空间中用二维高斯肤色模型计算肤色概率图，根据二维Ostu算法确定粒子群优化的目标函数，将积分图的方法用于粒子群优化中目标函数的计算，在有效地获取最佳阈值点的同时减少了计算量。实验表明，该方法能有效并且快速地分割出肤色区域。
위료경쾌지장부색구역종도상중분할출래，재이유Ostu방법적기출상，제출료일충장적분도화입자군우화상결합용우심조최우분할역치점적신방법。해방법통과대경과안색보상후적도편재YCbCr안색공간중용이유고사부색모형계산부색개솔도，근거이유Ostu산법학정입자군우화적목표함수，장적분도적방법용우입자군우화중목표함수적계산，재유효지획취최가역치점적동시감소료계산량。실험표명，해방법능유효병차쾌속지분할출부색구역。
To segment the skin color area faster, this paper puts forward a method to look for the best segmentation threshold point with integral image and particle swarm optimization based on the basic 2D Ostu method. The method uses two-dimen-sional gaussian skin model in the YCbCr color space with a color compensation picture to gain the skin probability graph, and then confirms the particle swarm optimization’s objective function by the 2D Ostu algorithm, and calculates the func-tion’s value with the integral image. The method can get the best threshold point effectively and can shorten the calcula-tion at the same time. Experiments show that the method can segment the skin color area effectively and quickly.