Research on the Design and Automatic Recognition Algorithm of Subsidence Marks for Close-Range Photogrammetry

Abstract

In China, traditional techniques for measuring structural subsidence cannot keep pace with the rapid development of critical national infrastructure such as the growing network of high-speed railways. Traditional monitoring methods using leveling instruments are inefficient and time consuming when monitoring structures like bridges and tunnels. Thus, a fast, economical, and more accurate and precise way to survey building subsidence is urgently needed to address this problem. This paper introduces a new close-range photogrammetry technique that deploys a fixed camera with tilt compensator to measure changes in height over small areas. A barcode subsidence mark that can be identified automatically during digital image processing replaces the leveling points used in traditional methods. Four experiments at different locations verified that results from the new method were stable and consistent with total station measurements. This approach is simple, inexpensive, and produces accurate and precise results as our evaluation results show.

Validation of a Method for Measuring the Position of Pick Holders on a Robotically Assisted Mining Machine’s Working Unit

“…A two-image method (stereophotogrammetry) is used for determining the spatial position. The density of the marker grid projected onto the reconstructed side surface was selected in such a way as to allow, on the one hand, sufficient accuracy in reproducing its shape (for the presented task) [24] and, on the other hand, reducing the amount of measurement data and thus eliminating the redundancy of the processed information, as is the case of, for example, in scanning. An enormous amount of redundant data would complicate the measurement procedure as well as increase the lead time, which would affect the timing of the robotic station waiting for the measurement result.…”

Characteristics of Deformation and Stability of Ultra-Deep Pit in Plateau Alluvial–Lacustrine Gravel Strata

“…A laboratory model of the ultra-deep pit containing certain simplifications was built. The monitoring points were set up along the top of the pit walls, and the monitoring lines were established in the surrounding ground [29,30]. Accurately positioned marks were The horizontal displacements on the southern and northern pit walls exhibited similar temporal variations to those on the eastern and western pit walls, and the difference between the maximum lateral deformation on long-edged sides and that on short-edged sides was small.…”

“…A laboratory model of the ultra-deep pit containing certain simplifications was built. The monitoring points were set up along the top of the pit walls, and the monitoring lines were established in the surrounding ground [29,30]. Accurately positioned marks were used to identify the monitoring points and lines as well as the reference points.…”

Barcode Recognition for Multistrip Lateral Flow Assay Reader

“…(9,10) In any case, the determination of a barcode area is essential for the equipment to recognize the barcodes for analysis. (5,(11)(12)(13)(14) When a common laser-scanning method is employed as the barcode scanner, a barcode area can be located by attaching scanners to each slot into which strips are mounted. However, this requires multiple scanning devices, resulting in the increased size and cost of the overall equipment.…”

“…Owing to the recent development of smartphone cameras, it is easy to obtain high-performance, high-resolution cameras that provide various standard interfaces such as mobile industry processor interface (MIPI) and USB, allowing the implementation of smartphone cameras in various applications including biomedical applications. (15)(16)(17)(18)(19)(20)(21) However, although there are many examples of barcode detection using a camera in logistics systems or outdoor environments, (11)(12)(13)22,23) it is difficult to find an example where a smartphone camera is physically integrated in bio-instruments. (7,9,10,24) In this paper, we present a method to recognize multiple barcodes within a single image acquired using a low-cost smartphone camera.…”