Periodic spine screening in teenagers is important for early detection of adolescent idiopathic scoliosis, a deformity characterized by an abnormal spinal curve and vertebral rotation. Conventional methods for measuring vertebral rotation involve exposure to radiation and can be complicated by challenges inherent to manual identification of spinal features. We propose a method for automatic measurement of vertebral rotation using a nonradiation method that is easy to administer and is not associated with risk. To measure the angle of vertebral rotation from a Moire image, which is nonradiation method, convolutional neural network is applied to estimate the spinal position. In addition, to measure the angle from the spinal position in the transverse plane, we generate a spinal model of a teenager to obtain spinal dimensions in the transverse plane. The angle of vertebral rotation method is valid, having high correlation with method using computed tomography. The angle of vertebral rotation is meaningful for pathological diagnosis of adolescent idiopathic scoliosis.

To achieve accurate and robust detection of fetal heads in US (ultrasound) images, this paper proposes a method that integrates a voting scheme and an improved iterative randomized Hough transform (IRHT) method. First, a skeleton image is extracted from the input US image by pre-processes. Next, the voting scheme, which applies the improved IRHT method to detect ellipses from the skeleton image, is repeated P times, in each of which, if the difference between each detected ellipse’s parameter values and each parameter values saved in the list is small, the accumulator of the nearest values in the list is incremented by one (voting); otherwise, the detected parameter values are appended to the list. Finally, the ellipse with the most voted values in the list is outputted as the final detection result. As a result of experiments that use 30 US images captured under different conditions, it turns out that the proposed method achieves a very high ellipse detection rate of 94.97%, which is much higher than IRHT and improved IRHT. In addition, some parameters concerning the proposed method such as the optimal value for P are experimentally explored.

This paper proposes a stereovision-based assistive system for the visually impaired. The system is composed of a conventional white cane, stereoscopic cameras, keypad-type controller, tactile device,laptop computer, and so forth. The system can not only detect obstacles, but also recognize seats that a visually impaired user can use to take a rest. Ordinarily, a user can use the system as a white cane. When the user instructs the system to detect obstacles or to recognize seats in the vicinity, the system attempts to find such objects. If the target objects are found in the field of view of the stereoscopic cameras, the tactile device provides vibration feedback. The proposed system was applied to actual scenes that included obstacles or seats. The experimental results indicated that the proposed system is promising as means of helping visually impaired users find obstacles and seats.

Secular change is an important factor to produce realistic computer graphics (CG) images. Rust generated over time on metals is an example of such secular change. The appearance of rust depends on the type of metal, on water adherence by rain or sea water, on the quantity of dissolved oxygen in water, and on effects of water flows. To our knowledge, there are no simulation models of rust that take into account the relevant chemical reaction processes. In the method proposed here, we perform a fluid simulation, calculate the water adherence and flow using three-dimensional models, and calculate the progression of corrosion from sites of adherence. This corrosion simulation takes into account conditions such as the amount of adherence and the relevant chemical reaction processes. As a result, we show that the mass loss for iron is close to the theoretical value, and that CG images are similar to those of actual rust.