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Adaptive Fine Distortion Correction Method for Stereo Images of Skin Acquired with a Mobile Phone

机译:用手机获取的皮肤立体图像的自适应细小失真校正方法

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摘要

With the development of the mobile phone, we can acquire high-resolution images of the skin to observe its detailed features using a mobile camera. We acquire stereo images using a mobile camera to enable a three-dimensional (3D) analysis of the skin surface. However, geometric changes in the observed skin structure caused by the lens distortion of the mobile phone result in a low accuracy of the 3D information extracted through stereo matching. Therefore, our study proposes a Distortion Correction Matrix (DCM) to correct the fine distortion of close-up mobile images, pixel by pixel. We verified the correction performance by analyzing the results of correspondence point matching in the stereo image corrected using the DCM. We also confirmed the correction results of the image taken at the five different working distances and derived a linear regression model for the relationship between the angle of the image and the distortion ratio. The proposed DCM considers the distortion degree, which appears to be different in the left and right regions of the image. Finally, we performed a fine distortion correction, which is difficult to check with the naked eye. The results of this study can enable the accurate and precise 3D analysis of the skin surface using corrected mobile images.
机译:随着手机的发展,我们可以获得皮肤的高分辨率图像,以观察其使用移动摄像机的详细功能。我们使用移动摄像头获取立体图像,以启用皮肤表面的三维(3D)分析。然而,由移动电话的镜头失真引起的观察到的皮肤结构中的几何变化导致通过立体声匹配提取的3D信息的低精度。因此,我们的研究提出了失真校正矩阵(DCM)来校正特写移动图像的细小失真,像素的像素。我们通过分析使用DCM校正的立体声图像中的对应点匹配结果来验证校正性能。我们还确认了在五个不同的工作距离下拍摄的图像的校正结果,并导出了用于图像角度与失真率之间的关系的线性回归模型。所提出的DCM认为失真程度,在图像的左侧和右侧区域似乎不同。最后,我们进行了一种细小的畸变校正,这很难用肉眼检查。该研究的结果可以使用校正的移动图像来实现皮肤表面的准确和精确的3D分析。

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