一种基于灰度倾向加权的Otsu目标检测法

An Improved Otsu Object Detection Method Based on Grayscale Preference Weighted

摘要:

通过引入灰度倾向参数和梯度谷值系数,提出一种改进的灰度倾向谷强调(GPVE)目标检测方法。灰度倾向参数使阈值更靠近目标灰度,梯度谷值系数使得阈值更靠近波谷。GPVE法在单双峰情况下都能得到理想的阈值。实验结果表明:Otsu,VE,NVE,WOV等方法分割得到的平均分割误差ME值都在0.2以上,而所提方法的ME值仅为0.007,采用该方法提高了图像分割的准确度,分割效果优于Otsu,VE,NVE,WOV等方法。

Abstract:

By introducing grayscale preference parameters and gradient valley coefficients, an improved grayscale preference valley emphasis (GPVE) method is proposed. The grayscale preference parameter makes the threshold show a tendency to approach the object gradation, and the gradient valley coefficient makes the threshold closer to the valley. GPVE method can achieve an ideal threshold when the histogram is unimodal and bimodal. The experimental results show that the average segmentation error ME value obtained by Otsu, VE, NVE, WOV and other methods is above 0.2, while the ME value of the proposed method is only 0.007. Thus the proposed GPVE method improves the accuracy of image segmentation and realizes a better segmentation effect.