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Automatic Red-eye Detection and Correction System for Mobile Devices

机译:移动设备自动红眼检测和校正系统

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This paper presents an automatic red-eye detection and correction system. In order to detect red eye, we propose to use two information sources: color around the eyes and eye's round shape. The color information is from the red, highlight, and skin masks. Eye-shape is from our proposed real-time 2-dimensional grouping algorithm called ARTS. Our correction method promises to a natural-looking result. We designed the hardware using Verilog HDL, and successfully built and tested it using an FPGA device, a USB interface board, and a two-megapixel CMOS sensor. With a TSMC 0.25 -μm ASIC library, the gate count was 325,167 gates, and the maximum data arrival time was 41.8 [MHz].
机译:本文提出了一种自动的红眼检测和校正系统。为了检测红眼,我们建议使用两个信息来源:眼睛周围的颜色和眼睛的圆形。颜色信息来自红色,突出显示和皮肤面罩。眼睛形状来自我们所提出的实时二维分组算法,称为艺术。我们的校正方法有望自然的结果。我们使用Verilog HDL设计了硬件,并使用FPGA设备,USB接口板和两百万像素CMOS传感器成功构建和测试。使用TSMC 0.25-μmASIC库,栅极计数为325,167门,最大数据到达时间为41.8 [MHz]。

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