Bowties and Hourglasses: Intersections of Double-Wedges Or: Stabbing and Avoiding Line Segments

Line and word segmentation is a key-step in any document image analysis system. It can be used for instance in handwriting recognition when separating words before their recognition. Line segmentation can also serve as a prior step before extracting the geometric characteristics of lines which are unique to each writer. Text line and word segmentation is not an easy task because of the following problems: 1) text lines do not all have the same direction in the handwritten text; 2) text lines are not always horizontal which makes their separation more difficult; 3) characters may overlap between successive text lines; 4) it is often confusing to distinguish between inter and intra word distances. In our method, line segmentation is done by using a smoothed version of the handwritten document which makes it possible to detect the main line components using a subsequent thresholding algorithm. The connected components of the resulting image are then assigned to a separate label which represents a line component. Then, each text region which intersects only with one line component is assigned to the same label of that line component. The Voronoi diagram of the image thus obtained is then computed in order to label the remaining text pixels. Word segmentation is performed by computing a generalized Chamfer distance in which the horizontal distance is slightly favored. This distance is subsequently smoothed in order to reflect the distances between word components and neglect the distance to dots and diacritics. Word segmentation is then performed by thresholding the distance thus obtained. The threshold depends on the characteristics of the handwriting. We have therefore computed several features in order to predict it, including: the sum of maximum distances within each line component, the number of connected components within the document and the average width and height of lines. The optimal threshold is then obtained by training a linear regression of those features on a training set of about 100 documents. This method achieved the best performance on the ICFHR Handwriting Segmentation Contest dataset reaching a matching score of 97.4% on line segmentation and 91% on word segmentation. The method has also been tested on the QUWI Arabic dataset reaching 97.1% on line segmentation and 49.6% on word segmentation. The relatively low performance of word segmentation in Arabic script is due to the fact that words are very close to each other with respect to English script. The proposed method tackles most of the problems of line and word segmentation and achieves high segmentation results. It can however be improved by combining it with a handwriting recognizer which will eliminates words which are not recognized.

Numerical investigation into the composite behaviour of over-deformed segmental tunnel linings strengthened by bonding steel plates

The application of the mechanized tunnelling has been extended in recent years. There are at present different approaches that are used in the design of segmental tunnel linings supported in mechanized tunnels. Even though segmental lining is utilized for mechanized tunnels, its behaviour is still quite unclear under in situ stress and there is a lack of data regarding the distribution of stresses inside segmental linings. So far no single effective calculation method exists for segmental lining design. The lack of clear solutions makes the use of segmental lining to be more expensive due to the adoption of greater safety factors. Therefore, a particular attention must be given in order to obtain data from monitored tunnels which permits to validate design methods. In this study, strain measurements, which were conducted during the construction of twin tunnels in the Bologna-Florence railway line, have been presented. The behaviour of segmental lining during the excavation and the influence of a new tunnel excavation on an existing tunnel have been shown through the measured data. The data are then compared with the results obtained with Einstein and Schwartz's method and Duddeck and Erdmann's method, which permits to highlight the fact that the two analytical methods underestimate structural forces induced in the segmental lining and then must be used with caution.

This research concentrates on reconstruction of the output line segments of the paper in [1]. The Line Segmenting module of [1] in some scenarios segments the alphabets and the associated matras of a line text in two separate line segments. These line segments are reconstructed using the Reconstruct Module to produce a line text with all its alphabets and its associated matras. This module uses one of the measures of dispersions, that is, standard deviation to accomplish reconstruction of output line segments. Then words are segmented from the line segments using WordSegmenting Module. This module uses one of the measures of central tendencies, i.e. mean and one of the measure of dispersions i.e, standard deviation to achieve word segmentation. Then characters are segmented from words using CharacterSegmenting Module.

Under the application of the fluctuating Tunnel Boring Machine (TBM) jack thrust and the non-uniformly distributed total pressure of the slurry around the lining, the bending and the shear deformation occur on the segmental lining along the longitudinal direction, which cause a stress concentration and increase the damage risk of the segmental tunnel lining. The analysis of the circular joint stiffness is a critical step during the evaluation of the stress state of the segmental lining so as to decrease the associated risk of damage. In order to investigate the lining rings and the circular joint separately, an integrated numerical model which is composed of segment elements and joint elements was developed. Furthermore, stiffness equations for describing in the detail the circular joint behaviour of the tunnel segmental lining are derived. The new stiffness equation of the circular joint is also used to analyse the segment lining behaviour based on a well-known indoor test result by the scientific literature, and satisfactory results were obtained. A simplified estimation of the bending stiffness of the circular joint based on the Boltzmann equation is then suggested in order to obtain quickly its calculation. Finally, based on a specific numerical model, the calculated joint stiffnesses are adopted to analyse the vertical displacement of a real case (The Ningbo metro tunnel in China). Through a developed sensitivity analysis, some useful suggestions are proposed to reduce the damage risk of the segmental lining.

Numerical study of the segmental tunnel lining behavior under a surface explosion – Impact of the longitudinal joints shape

Introduction: To supply safety in the tunnels, it is necessary to construct escape routes and emergency exits that are performed by locating cross passages. Methods: These passages connect two tunnels transversely and apply escape routes. Using temporary steel structures to supply the ring stability in practice and reinforced concrete frame to stabilize the ring permanently can be appropriate to form a solid frame that transfers the opened ring's load to the opening surroundings. In this paper, a 3D finite element simulation was performed to analyze the influence of opening construction in the segmental concrete lining and a temporary support system. Using the simulation, stress and deformation distribution of the steel frame, bolts, and segmental lining were obtained. Results: The results show that by increasing the number of bolts from 18 to 30, the induced stress in the steel frame and bolts decreased to 76 and 59 percent, respectively. In addition, the maximum displacement in the segmental lining and the maximum opening value of the joints decline to 62.7 and 75 percent, respectively. Conclusion: Finally, it can be concluded that the steel frame can be used as a temporary support system.

3D numerical study of the joint dislocation and spacing impacts on the damage of tunnel segmental linings

Automatic intersection identification and extraction are an important foundation for urban road network updates and traffic network analysis and modeling. Existing intersection extraction methods based on steering angles and stopping points suffer from inadequate sampling amounts and threshold settings. To address this problem, we propose a road network intersection automatic extraction method based on vehicle trajectory intersection clustering. First, the continuous trajectory segments are extracted from trajectory data based on the sampling interval. Second, the maximum reconstruction error method is developed to extract straight-line trajectory segments from continuous trajectory segments. The overlapped straight-line trajectory segments belonging to the same direction are merged to reduce the number of segments and enhance road network patterns. To further improve the calculation efficiency of the intersection points of straight-line segments, bounding box filtering and orthogonal filtering are used to filter the straight-line trajectory segments that do not have an intersection relationship. Finally, the obtained straight-line segment intersection points are clustered using a density peak clustering algorithm. The road intersections are automatically extracted using the clustering center. The experimental results on real vehicle trajectories in Lianyungang City show that the proposed method performs well on intersection recognition and calculation efficiency.

Segmentation is a very critical stage in the character recognition process as the performance of any character recognition system depends heavily on the accuracy of segmentation. Although segmentation is a well-researched area, segmentation of handwritten text is still difficult owing to several factors like skewed and overlapping lines, the presence of touching, broken and degraded characters, and variations in writing styles. Therefore, researchers in this area are working continuously to develop new techniques for the efficient segmentation and recognition of characters. In the character recognition process, segmentation can be implemented at the line, word, and character level. Text line segmentation is the first step in the text/character recognition process. The line segmentation methods used in the character recognition of handwritten documents are presented in this paper. The various levels of segmentation which include line, word, and character segmentation are discussed with a focus on line segmentation.KeywordsSegmentationOCRPattern recognitionLine segmentationWord segmentationCharacter segmentationTouching lines segmentationOverlapping lines segmentation

Recognition of geometric primitives such as line and arc helps in automatic conversion of line drawing document images into electronic form. A large number of raster to vector methods can be found in the literature. A line and arc segmentation contest was held in conjunction with the tenth IAPR International Workshop on Graphics Recognition (GREC 2013) for comparing performance of different methods on a uniform platform. The contest was broken down into two challenges: arc segmentation and line segmentation. The dataset includes engineering drawings (for arc segmentation challenge) and cadastral maps (for line segmentation challenge). Jianping Wu’s method got the highest score (0.541), hence the winner of the Arc Segmentation Contest. Liu Wenyin’s method, the only method participated in the line segmentation contest achieved 66 % segmentation accuracy.KeywordsGraphics recognitionLine drawingArc and line segmentation contestPerformance evaluation

When building tunnels using segmental lining, the segmental lining takes over the supporting role of the excavated soil. With the workspace in tunnel construction being very constricted the circular, segmental linings are divided into small segments called tubbings which are assembled by a tunnel boring machine. This kind of construction results in numerous longitudinal and circumferential joints. The loading situation for the longitudinal joints is typically dominated by the compressive normal forces combined with relatively small bending moments. The thickness of the tubbings usually depends on the longitudinal joints of the individual segments. The cross‐sectional area of the tubbings has to be reduced at the joints in order to avoid spalling of the concrete leading to higher compression in the joints themselves. The Institute of Structural Engineering of TU Wien developed a new reinforcement design for tubbings with strengthened longitudinal joints. With a patent application pending, the newly designed joints were manufactured and tested demonstrating that the TU Wien proposal significantly increases the load‐bearing capacity of the tubbings in comparison to conventional tubbing solutions. The very satisfying results, obtained from the large‐scale tests of the newly developed joint design, show great potential for the construction of tunnels with thinner tubbings in the near future.

Semi–analytical solution for ultimate bearing capacity of straight–jointed segmental tunnel lining

Experimental study on the effectiveness of strengthening over-deformed segmental tunnel lining by steel plates

Image-based line segment extraction plays an important role in a wide range of applications. Traditional line segment extraction algorithms focus on the accuracy and efficiency, without considering the integrity. Serious line segmentation fracture problems caused by image quality will result in poor subsequent applications. To solve this problem, a multi-constrained line segment extraction method, based on multi-scale image space, is presented. Firstly, using Gaussian down-sampling with a classical line segment detection method, a multi-scale image space is constructed to extract line segments in each image scale and all line segments are projected onto the original image. Then, a new line segment optimization and purification strategy is proposed with the horizontal and vertical distances and angle geometric constraint relationships between line segments to merge fracture line segments and delete redundant line segments. Finally, line segments with adjacent positions are optimized using the grayscale constraint relationship, based on normalized cross-correlation similarity criterion for realizing the second optimization of fracture line segments. Compared with mainstream line segment detector and edge drawing lines methods, experimental results (i.e., indoor, outdoor, and aerial images) indicate the validity and superiority of our proposed methods which can extract longer and more complete line segments.