论文标题
用于网络和移动应用程序开发的新型裸露检测算法
A Novel Nudity Detection Algorithm for Web and Mobile Application Development
论文作者
论文摘要
在我们当前的网络和移动应用程序开发中，运行时裸图像内容检测非常重要。本文介绍了用于Web和移动应用程序开发的运行时裸露检测方法。我们使用两个参数来检测图像的裸体内容。一个是皮肤像素的数量，另一个是面部区域。基于RGB的肤色模型，HSV颜色空间用于检测图像中的皮肤像素。 Google Vision API用于检测面部区域。根据皮肤区域和面部区域的百分比，图像是裸露的。该算法的成功存在于检测皮肤区域和面部区域。皮肤检测算法可以以低阳性速率准确地检测到皮肤95％，而用于Web和移动应用程序的Google Vision API可以在不到1秒的时间内准确地检测到面部99％。从实验分析中，我们可以看到所提出的算法可以准确检测到95％的图像裸体。
In our current web and mobile application development runtime nude image content detection is very important. This paper presents a runtime nudity detection method for web and mobile application development. We use two parameters to detect the nude content of an image. One is the number of skin pixels another is face region. A skin color model based on RGB, HSV color spaces are used to detect skin pixels in an image. Google vision api is used to detect the face region. By the percentage of skin regions and face regions an image is identified nude or not. The success of this algorithm exists in detecting skin regions and face regions. The skin detection algorithm can detect skin 95% accurately with a low false-positive rate and the google vision api for web and mobile applications can detect face 99% accurately with less than 1 second time. From the experimental analysis, we have seen that the proposed algorithm can detect 95% percent accurately the nudity of an image.
