Core point pixel-level localization by fingerprint features in spatial domain

<abstract> <p>Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on spatial domain features of fingerprint images from a completely different viewpoint to improve the fingerprint core point displacement problem of singular point detection. The method first defines new fingerprint features, called furcation and confluence, to represent specific ridge/valley distribution in a core point area, and uses them to extract the innermost Curve of ridges. The summit of this Curve is regarded as the localization result. Furthermore, an approach for removing false Furcation and Confluence based on their correlations is developed to enhance the method robustness. Experimental results show that the proposed method achieves satisfactory core localization accuracy in a large number of samples.</p> </abstract>

Human Tracking of a Crawler Robot in Climbing Stairs

There are many reports of secondary damage to crews during firefighting operations. One way to support and enhance their activities is to get robots to track them and carry supplies. In this paper, we propose a localization method for stairs that includes scene detection. The proposed method allows a robot to track a person across stairs. First, the scene detection autonomously detects that the person is climbing the stairs. Then, the linear model representing the first step of the staircase is combined with the person’s trajectory for localization. The method uses omnidirectional imaging and point clouds, and the localization and scene detection are available from any posture around the stairs. Finally, using the localization result, the robot automatically navigates to a posture where it can climb the stairs. Verification confirmed the accuracy and real-time capability of the method and demonstrated that the actual crawler robot autonomously chooses a posture that is ready for climbing.

Innovative Differential Magnetic Localization Method for Capsule Endoscopy to Prevent Interference Caused by the Geomagnetic Field

Wireless capsule endoscopy is an established medical application for the examination of the gastrointestinal tract. However, the robust and precise localization of these capsules is still in need of further scientific investigation. This paper presents an innovative differential magnetic localization method for capsule endoscopy to prevent interference caused by the geomagnetic field. The effect of changing the orientation of the capsule on the localization process was also examined. Simulations using COMSOL Multiphysics with the superimposed geomagnetic field were performed. The Levenberg–Marquardt algorithm was applied in MATLAB to estimate the position and orientation of the capsule. Comparing the proposed differential method with the absolute magnetic localization method under ideal conditions, the mean position and orientation errors were reduced by three orders in magnitude to less than 0.1 mm and 0.1∘ respectively. Even if sensor non-idealities are considered, the simulation-based results reveal that our proposed method is competitive with state-of-the-art geomagnetic compensation methods for static magnetic localization of capsule endoscopes. The achieved localization accuracy by applying the differential method is not dependent on the rotation of the localization system relative to the geomagnetic flux density under the made assumptions and the impact of the magnet orientation is neglectable. It is concluded that the proposed method is capable of preventing all interference whose components are approximately equal at all sensors with identical orientation.

On the accuracy of emitter localization method based on multipath exploitation in realistic scenarios

This study aims to evaluate the accuracy of a method proposed for passive localization of radar emitters around irregular terrains with a single receiver in Electronic Support Measures (ESM) systems. Previously, only the theoretical development of the localization method was targeted by the authors. In fact, this could be a serious concern in practice since there is no evidence about its accuracy under the real data gathered from realistic scenarios. Therefore, firstly, an accurate ray-tracing algorithm is adapted to the method in order to enable its implementation in practice. Then, scenarios are determined based on the geographic information system (GIS) map generated to collect high resolution digital terrain elevation data (DTED) as well as realistic localization problems for radar emitters. Next, the improved method is tested with simulations, and thus, its performance is verified for practical implementation in Electronic Warfare (EW) context for the first time in the literature. Lastly, based on the simulation results, the performance bounds of the method are also discussed.

Research on Target Localization Method of CRTS-III Slab Ballastless Track Plate Based on Machine Vision

In the construction of high-speed railway infrastructure, a CRTS-III slab ballastless track plate has been widely used. Anchor sealing is an essential step in the production of track plates. We design a novel automated platform based on industrial robots with vision guidance to improve the automation of a predominantly human-powered anchor sealing station. This paper proposes a precise and efficient target localization method for large and high-resolution images to obtain accurate target position information. To accurately update the robot’s work path and reduce idle waiting time, this paper proposes a low-cost and easily configurable visual localization system based on dual monocular cameras, which realizes the acquisition of track plate position information and the correction of position deviation in the robot coordinate system. We evaluate the repeatable positioning accuracy and the temporal performance of the visual localization system in a real production environment. The results show that the repeatable positioning accuracy of this localization system in the robot coordinate system can reach ±0.150 mm in the x- and y-directions and ±0.120° in the rotation angle. Moreover, this system completes two 18-megapixel image acquisitions, and the whole process takes around 570 ms to meet real production needs.