一种有效的正面图像民族识别计算机模型
Effective Computer Model For Recognizing Nationality From Frontal Image
摘要：
在深入研究的基础上，提出了一种新的有效的计算机模型，用于从正面图像候选人中提取人脸部分颜色，大小和距离。确定面部部分大小、颜色和距离取决于各种因素，包括图像质量、照明条件、旋转角度、遮挡和面部情绪。因此，首先我们需要检测图像上的人脸，然后将图像转换为真实输入。在此基础上，我们可以确定图像候选人的性别，人脸形状，关键点和人脸部位。最后，我们将根据与样本测量表数据库的大小和距离比较返回结果。当我们测量样本时，性别和脸型的图像之间存在很大差异。输入图像必须是正面图像，具有平滑的照明，没有任何旋转角度。该模型可用于军事，警察，国防，医疗保健和技术部门。最后，计算机可以从人脸图像中识别出国籍。
英文摘要：
We are introducing new effective computer model for extracting nationality from frontal image candidate using face part color, size and distances based on deep research. Determining face part size, color, and distances is depending on a variety of factors including image quality, lighting condition, rotation angle, occlusion and facial emotion. Therefore, first we need to detect a face on the image then convert an image into the real input. After that, we can determine image candidate gender, face shape, key points and face parts. Finally, we will return the result, based on the comparison of sizes and distances with the sample measurement table database. While we were measuring samples, there were big differences between images by their gender and face shapes. Input images must be the frontal face image that has smooth lighting and does not have any rotation angle. The model can be used in military, police, defense, healthcare, and technology sectors. Finally, Computer can distinguish nationality from the face image.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
