Image binarization method for markers tracking in extreme light conditions

Image binarization is one of the fundamental methods in image processing and it is mainly used as a preprocessing for other methods in image processing. We present an image binarization method with the primary purpose to find markers such as those used in mobile 3D scanning systems. Handling a mobile 3D scanning system often includes bad conditions such as light reflection and non-uniform illumination. As the basic part of the scanning process, the proposed binarization method successfully overcomes the above problems and does it successfully. Due to the trend of increasing image size and real-time image processing we were able to achieve the required small algorithmic complexity. The paper outlines a comparison with several other methods with a focus on objects with markers including the calibration system plane of the 3D scanning system. Although it is obvious that no binarization algorithm is best for all types of images, we also give the results of the proposed method applied to historical documents.

SMARTPHONE-BASED ANALYSIS OF CLOTH MASKS PORES SIZE

Until now, the world is still facing the spread of the SARS-CoV-2 virus that causes COVID-19. This virus can be transmitted from human to human through droplets, so more vigilance is needed to avoid contracting this virus. One of the steps to minimize the spread of Covid-19 is to wear a face mask. In practice, most people prefer to use cloth masks than disposable medical masks because they are cheap and reusable. Cloth pore size influences the filtering ability of the cloth masks. Therefore, it is necessary to analyze the efficiencies of the cloth masks. In this study, we developed a method for measuring the pores of a cloth mask using a smartphone. In this study, we developed a method for measuring the pores of a cloth mask using a smartphone. We used the camera zoom application on a smartphone and analyzed the image using image processing software, ImageJ. We appliedHuang's algorithm to adjust the image binarization threshold then calculated the Feret diameter as the pore size of the mask. According to the analysis, the pore size ranged from 0.133 to 0.232 mm, and the efficiency ranged from 77.4 to 82.6%.

The effect of phacoemulsification performed with vitrectomy on choroidal vascularity index in eyes with vitreomacular diseases

This study evaluated the effects of cataract surgery combined with pars plana vitrectomy (ppV) on choroidal vascularity index (CVI) in eyes with epiretinal membrane (ERM) and full thickness macular hole (FTMH). Medical records of 132 eyes with ERM or FTMH were retrospectively reviewed and classified into a ppV group and a ppV combined with cataract surgery group (phaco + ppV group). The CVI were measured at baseline, 1, 3 and 6 months after the surgery, using the selected swept-source (SS) optical coherence tomography (OCT) scan passing through the central fovea, which was then segmented into luminal and stromal area by image binarization. The mean CVI of phaco + ppV group were 61.25 ± 1.97%, 61.66 ± 1.81%, and 62.30 ± 1.92% at baseline, 1 and 3 months, respectively (p < 0.001). The mean CVI of ppV group were 62.69 ± 1.92%, 62.03 ± 1.51%, and 61.45 ± 1.71% at baseline, 1 and 3 months, respectively (p < 0.001). The final CVI were measured at 6 months and compared with the baseline CVI. The mean CVI of phaco + ppV group were 61.21 ± 1.99% at baseline and 60.68 ± 2.02% at 6 months (p < 0.001). The mean CVI of ppV group were 62.93 ± 1.70% at baseline and 61.77 ± 1.74% at 6 months (p < 0.001). Vitrectomy significantly decreases CVI in vitreomacular diseases possibly due to the removal of vitreomacular traction or postoperative oxygenation change in the eye. On the contrary, combined surgery of vitrectomy and cataract surgery significantly increases CVI in the early stage of postoperative period, which suggests choroidal vascular dilatation or congestion due to postoperative inflammation. Although the CVI were measured lower than the baseline in the end, more thorough inflammation control may be essential after combined surgery.

Layer contour characterization in additive manufacturing through image binarization

On-Machine Measurement adoption will be key to dimensional and geometrical improvement of additively manufactured parts. One possible approach based on OMM aims at using digital images of manufactured layers to characterize actual contour deviations with respect to their theoretical profile. This strategy would also allow for in-process corrective actions. This work describes a layer-contour characterization procedure based on binarization of digital images acquired with a flat-bed scanner. This procedure has been tested off-line to evaluate the influence of two of the parameters for image treatment, the median filter size (S f ) and the threshold value (T), on the dimensional/geometrical reliability of the contour characterization. Results showed that an appropriate selection of configuration parameters allowed to characterize the proposed test-target with excellent coverage and reasonable accuracy.