On intersecting straight line systems

Characterization and generation of straight line segments on triangular cell grid

Detection of straight lines in an image is a fundamental requirement for many applications in computer vision. We formulate the straight line detection task as an energy minimization problem. This formulation helps the detection of lines in a global manner in contrast to the local detection methods used in conventional algorithms. As a result the proposed straight line detection algorithm can handle virtually co-located straight lines, slightly curved lines and edge linking in a unified manner. In addition, due to its the global nature, the algorithm is not deceived by image noise giving rise to spurious line segments. Therefore, the proposed algorithm can robustly detect straight lines. The main component of the algorithm is formulating the energy to be minimized. The contribution to this energy function is less at a pixel which is a good candidate to be a member of an existing line segment depending on the directional gradients. A pixel choosing a part of a line segment is costly, but not impossible. This energy optimization is done using dynamic programming snakes. Since the algorithm is a global one and since no gradient calculations are used for local motion of nodes, our algorithm is robust. However, the optimization process takes a longer time than the existing straight line detection algorithms. Results are given for detecting straight lines in indoor environments

A line segment on the plane is guarded by n defenders. One invader wants to pass through the line segment, but he has to keep the distance from each defender no less than a given constant. All defenders can move along a straight line only with maximal speed 1. The invader can move on the whole plane with maximal speed greater than 1. Other than this, no kinematic or dynamic constraints are imposed on the defenders' and the invader's motions. The maximal length of the line segment which can be guarded by defenders is established in this paper.

To solve the problems of computational complexity and inaccuracy in classical vanishing point detection algorithms, such as the cascaded Hough transform, a vanishing point detection method based on constrained classification is proposed. First, the short line data are filtered to avoid interference in straight line detection, and then, the line segment is screened and classified by hierarchical clustering according to the image characteristics of the line segment and the variation pattern of angle similarity. Subsequently, Three types of straight line segments with the most significant angle differences are acquired. To prevent the optimization algorithm from getting stuck in the “wrong” local optimum neighborhood or failing to locate the global optimum, a set of constraints are set to further restrict the search. Afterward, the classified line segments are projected into a finite rhombic space, which are then quantified. The point with the maximum vote is eventually identified as the vanishing point. Experimental results show that the proposed method not only greatly reduces the computational complexity of vanishing points but also largely improves the accuracy of vanishing point detection.

Detection of transmission line is an important and challenging topic in low altitude flight. Different from the traditional transmission line detection method, in which the transmission line is detected based on the straight line, in order to extract the transmission line more completely, this paper proposes a new algorithm of transmission curve detection based on the morphological relation of finite element under the sky background. In the process of image processing, firstly, the whole sky background is extracted, and the line segment of the image under the sky background is extracted. Secondly, in the detection process, according to the idea of finite element, multiple groups of transmission line targets with certain curvature changes are regarded as composed of multiple groups of local line segment pairs. Using the morphological characteristics of the finite element line segment pairs of transmission line, different from other linear targets, line segment screening is carried out to remove the interference of pseudo linear targets. Finally, the finite element line pairs with obvious collinear characteristics are connected by collinear conditions to get the complete extracted transmission line. The experimental results show that this algorithm can detect the transmission line in the field of view and extract them completely.

Automatic road-side extraction from large scale imagemaps

In this paper, geometrical analysis is used to extract novel straight line segment features from the wings around the peaks of the Hough Transform (HT). Based on these features, a practical segment detection method is proposed which has the ability to determine complete straight line segment parameters including the location of the center, length, slope and the Euclidean distance to the origin. The proposed method does not rely on edge point verification in the image space, i.e., the complete set of segment features are determined only using the information embodied in the HT data. The proposed method can distinguish between highly collinear straight line segments. Segment detection is robust to disturbing edge points, especially ones collinear with the object. A predefined collinear segment resolution that provides a theoretical criterion to determine straight line contiguity is derived. Image processing and analysis experiments show consistent robust performance.

For decades, the slide drilling system (SDS) has played a critical role in the area of directional drilling. Drilling in the sliding mode is much more time-consuming than drilling in the rotating mode for a SDS. Therefore, it generally takes more time to drill a curved wellbore segment than a straight segment of the same length. Based on this fact, a novel wellbore trajectory design for SDSs is proposed in this paper to reduce the total drilling time and improve economy. The basic idea of our strategy is to replace a long curved wellbore section, e.g., the build-up and drop-off sections, with a series of short circular-arc and straight-line segments in the design stage. Assuming that rotating and sliding modes are only used for straight-line and circular-arc segments, respectively, the total drilling time is reduced by increasing the average rate of penetration. Therefore, the problem lies in how to replace a long circular arc with multiple short circular arcs and straight lines to minimize the total drilling time, which is the aim of this research. In this paper, a piecewise trial strategy is proposed, where the optimized wellbore trajectory is generated by adding circular-arc and straight-line segments with equal length one by one according to the “line first” principle. This strategy converts the original optimization problem, which involves both combinatorial and parameter optimization of unknown dimension, to a much easier one, where there are only three design variables and one set of constraint equations. Due to the multimodal characteristics of the objective function, genetic algorithm (GA) is adopted to obtain the optimal solution. A great reduction of the drilling time is obtained by applying our method to two typical cases, which shows a clear potential for future field applications.

Structural forces in segmental linings: process-oriented tunnel advance simulations vs. conventional structural analysis

Representation graphique d'une nouvelle forme linearisee de l'equation de l'isotherme de Langmuir

This paper presents an effective method to automatically segment and fit the edge contour curve data of a picture into straight line segments, circular arc segments or elliptical arc segments. Firstly, the curvature of each point is calculated, and the curvature change breakpoints are found to distinguish between straight lines, circular arcs and elliptical arcs; then, circular arc segments and elliptical arcs are distinguished by the change degree of curvature of adjacent points, and the automatic segmentation of contour edges is realized. Finally, the circular arc segment and elliptic arc segment are fitted by least squares method, based on which the length of the straight line, the direction angle of the circular arc, the rotation angle of the elliptic arc and other related information are calculated. The results show that our model can better identify the feature texture information of image edges.

Straight line programs are essentially sequences of assignment statements. A general program consists of straight line segments with flow of control between these segments. The interfaces between a straight line segment and the rest of the program place constraints on register allocations for the segment. These constraints may render a register allocation for a straight line program unrealizable. An algorithm is given to determine if a register allocation for a straight line program is realizable. It is shown that the algorithm takes 0(n3) steps, where n is the number of statements in the program. An unrealizable assignment may be made realizable by introducing stores into memory at appropriate points. It is shown how the minimum number of such stores may be found.

In the machining of sculptured surfaces, five‐axis CNC machine tools provide more flexibility to realize the cutter position as its axis orientation spatially changes. Conventional five‐axis machining uses straight line segments to connect consecutive machining data points, and uses linear interpolation to generate command signals for positions between end points. Due to five‐axis simultaneous and coupled rotary and linear movements, the actual machining motion trajectory is a non‐linear path. The non‐linear curve segments deviate from the linearly interpolated straight line segments, resulting in a non‐linearity machining error in each machining step. These non‐linearity errors, in addition to the linearity error, commonly create obstacles to the assurance of high machining precision. In this paper, a novel methodology for solving the non‐linearity errors problem in five‐axis CNC machining is presented. The proposed method is based on the machine type‐specific kinematics and the machining motion trajectory. Non‐linearity errors are reduced by modifying the cutter orientations without inserting additional machining data points. An off‐line processing of a set of tool path data for machining a sculptured surface illustrates that the proposed method increases machining precision.

Tables are one of the best ways to synthesize information such as statistical results, key figures in documents. In this article we focus on the extraction of materialized tables in document images, in the particular case where acquisition noise can disrupt the recovering of the table structures. The sequential printings/scannings of a document and its deterioration can lead to “broken” lines among the materialized segments of the tables. We propose a method based on the search for straight line segments in documents, relying on a new image transform that locally defines primitives well suited for pattern recognition and on a proposed theoretical model of lines in order to confirm their presence among a set of confident potential line parts. The extracted straight line segments are then used to reconstruct the table structures. Our approach has been evaluated both from quality and stability points of view.

Extracting bars (straight line segments) from a binary image is a first processing step in a system for understanding engineering drawings as well as other applications such as robotics [1]. A novel algorithm — the Orthogonal Zig-Zag (OZZ) has been developed and implemented. The underlying idea of OZZ is selective processing, or focus of attention. The binary input image is scanned intermittently and rather sparsely, but nevertheless all the necessary information needed to detect bars is extracted. Black pixels constitute a small fraction of the input drawing. Of these pixels, OZZ processes only a small fraction, resulting in both a dramatic reduction in both space and time compared to HT.