Structural Recognition for Table-Form Documents Using Relaxation Techniques

1998 ◽  
Vol 12 (07) ◽  
pp. 985-1005 ◽  
Author(s):  
Chi-Fang Lin ◽  
Cheng-Yi Hsiao
Keyword(s):  
Relaxation Techniques ◽  
Line Pattern ◽  
Line Segments ◽  
Line Extraction ◽  
Matching Process ◽  
Recognition Phase ◽  
Structure Recognition ◽  
Extraction Algorithm ◽  
Novel Method ◽  
Line Patterns

A novel method is proposed in this study to recognize the line structure of table-form documents, e.g. telephone bills and office documents. The line structures of table-form documents are mainly composed of horizontal and vertical line segments. By treating the segment structure as line patterns, the problem of structure recognition is turned out to be the searching of line pattern matching, which can be solved by adopting the technique of relaxation. The proposed method consists of a learning phase and a recognition phase. In the former phase, line structures of various kinds of table-form documents are taken as templates and are extracted through a line extraction algorithm, in which an unique number functioning as a form ID is assigned to each line pattern. In the latter, by adopting the method of relaxation, the line pattern of the testing document is matched to those patterns created in the previous phase and the form ID of the best matching is chosen as the ID of the testing document. To increase the performance of the proposed method, an algorithm was presented to reduce the number of line segments in the matching process. The experimental results reveal the practicability of the proposed methods.

scholarly journals Fast plane segmentation with line primitives for RGB-D sensor

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141666584 ◽  
Author(s):  
Lizhi Zhang ◽  
Diansheng Chen ◽  
Weihui Liu
Keyword(s):  
Point Cloud ◽  
Computational Cost ◽  
Data Sets ◽  
Line Segments ◽  
Line Extraction ◽  
Extraction Algorithm ◽  
Segmentation Approach ◽  
On Line

This article presents a fast and robust plane segmentation approach for RGB-D type sensor, which detects plane candidates by line segments extracted from 2-D scanline projected from row or column points. It neither requires high computation to calculate local normals for the entire point cloud as most of approaches do nor randomly chooses plane candidates such as RANSAC-like approaches. First, a line extraction algorithm is utilized to extract line segments. Second, the plane candidates are detected by estimating local normal of points lying on line segments. Finally, the plane having most inlier is recursively extracted from the plane candidates as the result plane. Experiments were conducted with different data sets and the segmentation performances were evaluated quantitatively and qualitatively. We demonstrated the efficiency and robustness of our proposed approach, especially in the none plane scenario, the approach needs little computational cost.

A Hybrid Model for Emotion Detection from Text

2017 ◽  
Vol 7 (1) ◽  
pp. 32-48 ◽  
Author(s):  
Samar Fathy ◽  
Nahla El-Haggar ◽  
Mohamed H. Haggag
Keyword(s):  
Semantic Similarity ◽  
Hybrid Model ◽  
Semantic Analysis ◽  
Main Idea ◽  
Object Extraction ◽  
Emotion Detection ◽  
Suggested Approach ◽  
Matching Process ◽  
Extraction Algorithm ◽  
Input Sentence

Emotions can be judged by a combination of cues such as speech facial expressions and actions. Emotions are also articulated by text. This paper shows a new hybrid model for detecting emotion from text which depends on ontology with keywords semantic similarity. The text labelled with one of the six basic Ekman emotion categories. The main idea is to extract ontology from input sentences and match it with the ontology base which created from simple ontologies and the emotion of each ontology. The ontology extracted from the input sentence by using a triplet (subject, predicate, and object) extraction algorithm, then the ontology matching process is applied with the ontology base. After that the emotion of the input sentence is the emotion of the ontology which it matches with the highest score of matching. If the extracted ontology doesn't match with any ontology from the ontology base, then the keyword semantic similarity approach used. The suggested approach depends on the meaning of each sentence, the syntax and semantic analysis of the context.

Research on TV Goniometer Object Extraction Algorithm Based on Threshold Segmentation

2014 ◽  
Vol 889-890 ◽  
pp. 1093-1098
Author(s):  
He Chen ◽  
Nan Li ◽  
Tian Chen Huang ◽  
Rong Xia Duan
Keyword(s):  
Optimal Algorithm ◽  
Detection System ◽  
Detection Algorithm ◽  
Field Of View ◽  
Object Extraction ◽  
Gray Level ◽  
Line Extraction ◽  
Standard Signal ◽  
Extraction Algorithm ◽  
Target Extraction

In the TV goniometer detection system, to play the signal and field of view points line extraction is a key link in the process of parameter detection. Combination of target processing requirements, this article will target extraction algorithm based on gray level threshold and edge detection algorithm is studied, and through the experimental analysis to select the optimal algorithm was applied to the detection of TV goniometer; According to the characteristics of the standard signal and view points, lines, and put forward the corresponding methods of target recognition, and is verified through experiments

scholarly journals A line segment extraction algorithm using laser data based on seeded region growing

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141875524 ◽  
Author(s):  
Haiming Gao ◽  
Xuebo Zhang ◽  
Yongchun Fang ◽  
Jing Yuan
Keyword(s):  
Line Segment ◽  
Region Growing ◽  
Superior Performance ◽  
Two Dimensional ◽  
Line Segments ◽  
Seeded Region Growing ◽  
Extraction Algorithm ◽  
Laser Data ◽  
Split And Merge ◽  
2D Data

This article presents a novel line segment extraction algorithm using two-dimensional (2D) laser data, which is composed of four main procedures: seed-segment detection, region growing, overlap region processing, and endpoint generation. Different from existing approaches, the proposed algorithm borrows the idea of seeded region growing in the field of image processing, which is more efficient with more precise endpoints of the extracted line segments. Comparative experimental results with respect to the well-known Split-and-Merge algorithm are presented to show superior performance of the proposed approach in terms of efficiency, correctness, and precision, using real 2D data taken from our hallway and laboratory.

Automatic boundary extraction from magnetic field data using triangular meshes

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. J47-J60 ◽  
Author(s):  
Nathan Leon Foks ◽  
Yaoguo Li
Keyword(s):  
Magnetic Field ◽  
Synthetic Data ◽  
Magnetic Data ◽  
Lake Area ◽  
Boundary Extraction ◽  
Data Set ◽  
Magnetic Field Data ◽  
Line Segments ◽  
Extraction Algorithm ◽  
The Magnetic Field

Boundary extraction is a collective term that we use for the process of extracting the locations of faults, lineaments, and lateral boundaries between geologic units using geophysical observations, such as measurements of the magnetic field. The process typically begins with a preprocessing stage, where the data are transformed to enhance the visual clarity of pertinent features and hence improve the interpretability of the data. The majority of the existing methods are based on raster grid enhancement techniques, and the boundaries are extracted as a series of points or line segments. In contrast, we set out a methodology for boundary extraction from magnetic data, in which we represent the transformed data as a surface in 3D using a mesh of triangular facets. After initializing the mesh, we modify the node locations, such that the mesh smoothly represents the transformed data and that facet edges are aligned with features in the data that approximate the horizontal locations of subsurface boundaries. To illustrate our boundary extraction algorithm, we first apply it to a synthetic data set. We then apply it to identify boundaries in a magnetic data set from the McFaulds Lake area in Ontario, Canada. The extracted boundaries are in agreement with known boundaries and several of the regions that are completely enclosed by extracted boundaries coincide with regions of known mineralization.

A Novel Line Segments Extraction Algorithm with Variant Constraints

2014 ◽  
Vol 529 ◽  
pp. 650-654
Author(s):  
Yong Gang He ◽  
Xiong Zhu Bu ◽  
Mao Jun Fan ◽  
Jun Hu
Keyword(s):  
Signal Processing ◽  
Line Segment ◽  
Array Signal Processing ◽  
Processing Method ◽  
Line Segments ◽  
Signal Processing Method ◽  
Extraction Algorithm

In the domain of CAM and AI, line segment extraction algorithm play an important role. In order to extract line segments in different degree of curvature and continuum, construct the flexible and variant linearization and continuum constraints by the array signal processing method. And through the setting dimension of image unit, extract line segments satisfying the constraints in different degrees. At the last some experiments on true images demonstrate the roles of flexible parameters and the efficiency of the algorithm.

Adaptive Line Extraction for Slam Line Based Applications in Unknown Environments

2011 ◽  
Vol 403-408 ◽  
pp. 2057-2064
Keyword(s):  
Mobile Robot ◽  
Laser Scanner ◽  
Line Extraction ◽  
International Conference ◽  
Unknown Environments ◽  
Extraction Algorithm ◽  
Ieee International Conference

Paper has been removed due to plagiarism. The original was published in the Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics, Bangkok, Thailand, February 21 - 26, 2009. Recursive Line Extraction Algorithm from 2D Laser Scanner Applied to Navigation a Mobile Robot, Mohammad Norouzi, Mostafa Yaghobi, Mohammad Rezai Siboni, Mahdi Jadaliha

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