This article uses the three-dimensional (3D) modeling software Maya and the 3D interactive software Unity3D to develop an interactive teaching system that integrates the display of the human brain, the display of the principle pathology of cerebral thrombosis, and the simulation of stent surgery in the brain. The use of this system can result in unlimited learning by multiple people, avoiding shortcomings such as insufficient resources, and strengthening the characteristics of interaction. For human brain models, functions such as zoom-in, rotation, and observation of a single part can be implemented, and text descriptions are provided. For the demonstration of cerebral thrombosis, animation is provided for simulation. For intra-brain stent surgery, the system can automatically demonstrate the surgical process, and it can be actually operated by the user, thereby enhancing the convenience and fun of student learning. This system uses Unity3D software as the main development tool. It uses the software’s advanced lighting system, particle system, and algorithms such as edge detection and screen post effects to establish the main frame of the system. It utilizes C # language for programming, thus enriching the functions of the system. On testing, the virtual interactive teaching system realized by the above method exhibits high interactivity, fun, and practicability.

In this article, a passive haptic learning method for Taiwanese Braille writing was developed for visually impaired individuals through the employment of an effective user-friendly learning strategy. This system was designed with portability and low cost by applying the learning concept of passive haptic learning. This system designed a pair of gloves for visually impaired people to study Braille writing. Furthermore, we also designed a Braille writing teaching system for visually impaired people to learn and practice the Braille writing. Depending on the learning content, the corresponding vibration motors on the glove fingertips vibrate to produce the Taiwan Braille input gestures. The visually impaired people then feel tactile vibration feedback from the glove fingertips. In addition, the corresponding auditory feedback is provided from the Braille writing teaching system. After receiving a series of tactile vibration feedback, user’s finger muscles could memorize the corresponding Braille input gestures by the passive haptic learning. In the practice mode, the teaching system randomly selects practice content and announces the selected content in an auditory manner. Visually impaired users must then input the corresponding Braille codes by using the Braille writing input module. This mode can further reinforce users’ memorization of correct Braille codes for Mandarin characters.

Virtual reality head-mounted displays (VR HMDs) can provide three-dimensional content to increase user immersion that is relatively acceptable. However, user interactions with VR HMDs often do not satisfy a virtual environment. In this article, the authors propose a smart human–computer interaction technique that runs on VR HMDs and Leap Motion. In this study, they focused on improving interaction methods for VR content and providing interfaces and information necessary for the operation of such content in a user-friendly manner, which should reduce fatigue and dizziness. To this end, they propose and validate a smart head-up display that is suitable for VR content. Specifically, a virtual head-up display (HUD) was designed and optimized for use with VR HMD and Leap Motion technologies. Additionally, they present comparative performance tests to validate the proposed system.

This study represents an attempt to solve the problem of color reproduction and identification for the prevention of stamp forgery. Generally, printed images are converted to halftone dot patterns by using a raster image processor. The amplitude-modulated dots of each separated color plane have a consistent shape such as conventional round, square, ellipse, or diamond shape; error diffusion occurs in frequency-modulated dots. To achieve anti-counterfeiting properties for stamp reproduction, two methods are proposed to obtain difficult-to-replicate dot structures and to provide corresponding color management methods. The first method involves arranging different dot shapes in different areas of an image. Color consistency is achieved using a virtual gray balance method. However, color differences are visible when two dot types are assigned to adjacent areas with similar colors. The second method is a two-stage screening method. The first screening stage defines different micro-regions in the image, which are then combined with the continuous-tone image again in the second screening step to assign different dot patterns to different micro-regions. This approach not only provides anti-counterfeiting ability but also ensures color consistency and allows controlling color quality using one ICC profile.

ENT-flexible endoscopes are important for nasopharyngoscopy examinations. However, hospitals do not apply standardized tests to assess the image quality of the endoscopes they use or consider to purchase. The authors evaluated the Rez Checker Target Nano Matte, a test chart that was designed by Image Science Associates for this purpose. The target was placed in a custom setup designed to position the endoscope tip at a distance of 3.0 cm. The primary metrics, including opto-electronic conversion function, noise, modulation transfer function, and color fidelity, were measured using a custom MATLAB script for the Pentax VNL9-CP, Olympus ENF-V4, and Xion XN HD flexible endoscope. For each of these endoscopes, three examples were measured ten times. In addition, 38 Pentax VNL9-CP endoscopes that are regularly used in their clinic were measured to validate this method for the purpose of quality control. They found that the Rez Checker Target Nano Matte can be used to reliably assess image performance metrics for both procurement and quality control. Whether better image quality also improves the diagnostic accuracy of the ENT-specialist seems plausible, but has to be established.

In this study, the authors generate panoramic images using feature-based registration for drone-based aerial thermal images. In the case of drone aerial images, the distortion of the photographing angle due to the unstableness in the shooting altitude deteriorates the performance of the stitching. Furthermore, for the thermal aerial images, the same objects photographed at the same time zone may have different colors due to the relative temperature, which may lead to a more severe condition to be stitched. Applying the scale-invariant feature transform descriptor, they propose a posteriori outlier rejection scheme to estimate the hypothesis of the mapping function for the stitching of consecutive thermal aerial images. By extension of the method of optimal choice of initial candidate inliers (OCICI) and a posteriori outlier rejection scheme using cross-correlation calculus, the authors obtained elaborate stitching of thermal aerial images. Their proposed method is numerically verified for its quality by comparing it with other possible approaches of post-outlier rejection treatments employed of OCICI. Also, after the Poisson blending using the finite difference method is conducted, the stitching performance is compared with some benchmark software such as Matlab-toolbox, OpenCV, Autopano Giga, Hugin, and PTGui.

With advances in technology, photo booths equipped with automatic capturing systems have gradually replaced the identification (ID) photo service provided by photography studios, thereby enabling consumers to save a considerable amount of time and money. Common automatic capturing systems employ text and voice instructions to guide users in capturing their ID photos; however, the capturing results may not conform to ID photo specifications. To address this issue, this study proposes an ID photo capturing algorithm that can automatically detect facial contours and adjust the size of captured images. The authors adopted a deep learning method (You Only Look Once) to detect the face and applied a semi-automatic annotation technique of facial landmarks to find the lip and chin regions from the facial region. In the experiments, subjects were seated at various distances and heights for testing the performance of the proposed algorithm. The experimental results show that the proposed algorithm can effectively and accurately capture ID photos that satisfy the required specifications.