The Detection and Realization of Data Matrix Code by Accurate Locating

2014 ◽  
Vol 6 (4) ◽  
pp. 35-42
Author(s):  
Lingling Li ◽  
Yaoquan Yang ◽  
Tao Gao
Keyword(s):  
Detection Method ◽  
Initial Position ◽  
Code Region ◽  
Corner Detection ◽  
Data Matrix ◽  
Accurate Data ◽  
Success Rates ◽  
Brightness Difference ◽  
Barcode Recognition ◽  
And Cluster Analysis

This paper proposes a Data Matrix code recognition technology, which includes initial position, rotation correction and final accurate locating based on corner detection and cluster analysis. The accurate Data Matrix code region can be obtained from the complex background. By detection method proposed in this paper, the success rates of various types of Data Matrix barcode recognition are improved, especially in the test with the brightness difference, and the effect is very obvious, which embodies the characteristics of Data Matrix code used for Internet of Things. It can also more effectively find the area of uneven illumination. The improved algorithm is more stable and adaptive, so as to improve the success rate of recognition.

scholarly journals Efficient 3D stereo vision stabilization for multi-camera viewpoints

2019 ◽  
Vol 8 (3) ◽  
pp. 882-889
Author(s):  
Sharif Shah Newaj Bhuiyan ◽  
Othman O. Khalifa
Keyword(s):  
Stereo Vision ◽  
Linear Order ◽  
Spanning Tree ◽  
Detection Method ◽  
Corner Detection ◽  
Geometric Transformation ◽  
Image Stabilization ◽  
Tree Algorithm ◽  
Stabilization Process ◽  
Key Points

In this paper, an algorithm is developed in 3D Stereo vision to improve image stabilization process for multi-camera viewpoints. Finding accurate unique matching key-points using Harris Laplace corner detection method for different photometric changes and geometric transformation in images. Then improved the connectivity of correct matching pairs by minimizing the global error using spanning tree algorithm. Tree algorithm helps to stabilize randomly positioned camera viewpoints in linear order. The unique matching key-points will be calculated only once with our method. Then calculated planar transformation will be applied for real time video rendering. The proposed algorithm can process more than 200 camera viewpoints within two seconds.

Multi-feature SUSAN corner detection method

2005 ◽  
Author(s):  
Xun Wang ◽  
Jianqiu Jin ◽  
Yun Ling ◽  
Zhaoyi Jiang
Keyword(s):  
Detection Method ◽  
Corner Detection

Direct Part Mark Bar Code Image Preprocessing

2015 ◽  
Vol 7 (3) ◽  
pp. 13-24
Author(s):  
Lingling Li ◽  
Tao Gao ◽  
Yaoquan Yang
Keyword(s):  
Recognition Algorithm ◽  
Code Region ◽  
Data Matrix ◽  
Background Region ◽  
Vertical Projection ◽  
Transform Method ◽  
Color Processing ◽  
Low Contrast ◽  
Bar Code ◽  
Intensity Changes

Due to factors such as ambient light and metal materials, the collected industrial DPM bar code images may exist uneven illumination, low contrast, color of background area is darker than bar code region and other harsh issues, while the existing 2D code recognition device can only recognize the type which bar code area color is darker than background region. Therefore, the quality of preprocessing effect is the key point to subsequent recognition algorithm. In this paper, the homomorphic filtering method is used to weaken the influence of uneven illumination firstly, which will enhance the image contrast degree. Then do horizontal and vertical projection, find the points with greater intensity changes in both directions, make the image into blocks, again use the classic Kittler binarization algorithm on each block, then use mathematical morphology method to standardize the dot data matrix images. Finally, an improved Hough transform method is used to detect the ‘L' type finder pattern accurately, then find its pixel value, if color of the background region is darker than the bar code area, do invert-color processing. The processing results of a set of industrial DPM bar code images confirm the effectiveness of the proposed method.

Improved FAST Corner Detection Based on Harris Algorithm for Chinese Characters

2013 ◽  
Vol 850-851 ◽  
pp. 767-770 ◽  
Author(s):  
Na Yao ◽  
Tie Cheng Bai ◽  
Jie Chen
Keyword(s):  
Feature Extraction ◽  
Fast Algorithm ◽  
Detection Rate ◽  
Detection Method ◽  
Corner Detection ◽  
Detection Methods ◽  
Chinese Characters ◽  
Line Segments ◽  
Running Time ◽  
Shape Feature Extraction

According to the characteristics of Chinese characters image, we propose an improved corner detection method based on FAST algorithm and Harris algorithm to improve detection rate and shorten the running time for next feature extraction in this paper. The image of Chinese characters is detected for corners using FAST algorithm Firstly. Second, computing corner response function (CRF) of Harris algorithm, false corners are removed. The corners founded lastly are the endpoints of line segments, providing the length of line segments for shape feature extraction. The proposed method is compared with several corner detection methods over a number of images. Experimental results show that the proposed method shows better performance in terms of detection rate and running time.

Corner detection method based on wavelet transform

2001 ◽  
Author(s):  
Xiaoming Peng ◽  
Chengping Zhou ◽  
Mingyue Ding
Keyword(s):  
Wavelet Transform ◽  
Detection Method ◽  
Corner Detection
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