Identification and Documentation of Auricle Defects using Three-dimensional Optical Measurements.

Auricle defects are important and common occurrences in forensic medicine. The accurate measurement and assessment of auricle defects is key to identifying and evaluating injury, and the currently available methods are known to be labor intensive and inaccurate. In this paper, we introduce an identification and documentation of auricle defects solution, which consists of an optical three-dimensional (3D) method and an effective algorithm to calculate the maximum projection area and identify auricle defects. In this study, three separate examiners measured 40 auricles of 20 adults using 3D optical measurement and two other commonly used methods to investigate the validity and representative reliability of 3D optical measurement for auricle defect identification. Based on the statistical analysis, the 3D measurement method is valid and showed a better reliability than the reference methods. We also present a representative auricle defect identification case using the proposed 3D optical measurement method. The study concludes that the optical 3D measurement method is a reliable and effective tool for auricle defect identification.

High-speed FPGA-based phase measuring profilometry architecture.

This paper proposes a high-speed FPGA architecture for the phase measuring profilometry (PMP) algorithm. The whole PMP algorithm is designed and implemented based on the principle of full-pipeline and parallelism. The results show that the accuracy of the FPGA system is comparable with those of current top-performing software implementations. The FPGA system achieves 3D sharp reconstruction using 12 phase-shifting images and completes in 21 ms with 1024 × 768 pixel resolution. To the best of our knowledge, this is the first fully pipelined architecture for PMP systems, and this makes the PMP system very suitable for high-speed embedded 3D shape measurement applications.

Rapid and automatic 3D body measurement system based on a GPU-Steger line detector.

This paper proposes a rapid and automatic measurement system to acquire a 3D shape of a human body. A flexible calibration method was developed to decrease the complexity in system calibration. To reduce the computation cost, a GPU-Steger line detector was proposed to more rapidly detect the center of the laser pattern and at subpixel level. The processing time of line detection is significantly shortened by the GPU-Steger line detector, which can be over 110 times faster than that by CPU. The key technologies are introduced, and the experimental results are presented in this paper to illustrate the performance of the proposed system. The system can be used to measure human body surfaces with nonuniform reflectance such as hair, skin, and clothes with rich texture.