Image binarization algorithm using GPU for woodworking industry applications

2017 ◽  
Author(s):  
A. Petrov ◽  
V. Pelevin
Keyword(s):  
Image Binarization ◽  
Industry Applications ◽  
Binarization Algorithm

Image binarization method for markers tracking in extreme light conditions

2021 ◽  
pp. 1-15
Author(s):  
Milan Ćurković ◽  
Andrijana Ćurković ◽  
Damir Vučina
Keyword(s):  
Image Processing ◽  
3D Scanning ◽  
Scanning System ◽  
Image Size ◽  
Image Binarization ◽  
Basic Part ◽  
Binarization Algorithm ◽  
Binarization Method ◽  
Scanning Systems ◽  
Time Image

Image binarization is one of the fundamental methods in image processing and it is mainly used as a preprocessing for other methods in image processing. We present an image binarization method with the primary purpose to find markers such as those used in mobile 3D scanning systems. Handling a mobile 3D scanning system often includes bad conditions such as light reflection and non-uniform illumination. As the basic part of the scanning process, the proposed binarization method successfully overcomes the above problems and does it successfully. Due to the trend of increasing image size and real-time image processing we were able to achieve the required small algorithmic complexity. The paper outlines a comparison with several other methods with a focus on objects with markers including the calibration system plane of the 3D scanning system. Although it is obvious that no binarization algorithm is best for all types of images, we also give the results of the proposed method applied to historical documents.

scholarly journals A ROBUST BINARIZATION AND TEXT LINE DETECTION IN HISTORICAL HANDWRITTEN DOCUMENTS ANALYSIS

2016 ◽  
pp. 154-161
Author(s):  
Jakub Leszek Pach ◽  
Piotr Bilski
Keyword(s):  
Fifteenth Century ◽  
Hough Transform ◽  
Connected Components ◽  
Image Binarization ◽  
Handwritten Documents ◽  
Local Maxima ◽  
Novel Method ◽  
Block Based ◽  
Binarization Algorithm ◽  
Selection Of

In this paper, we present a novel method of detecting text lines in handwritten documents based on the Block-Based Hough Transform. To maximize its efficiency, the robust binarization algorithm was applied. It is based on the Gaussian filtering and tackles the non-uniform luminance. The proposed technique consists of three steps: preprocessing, detecting of potential text lines and eliminating the false ones. The first step covers the image binarization, extraction of connected components and selection of supporting connected components based on the local maxima in the vertical histogram stripes. Secondly, the appropriate subset of connected components supplemented by one-point components is selected. Finally, the block-based Hough transform is applied to detect potential text lines and found the ones identified incorrectly. The proposed method is applied to the analysis of the fifteenth century Latin manuscripts. Our approach is more effective than the traditional ones, in the best cases by twenty percent.

An Novel Binarization Algorithm Based on Wavelet and an Optimal Box Counting Fractal Dimension for MEMS Measurement

2013 ◽  
Vol 718-720 ◽  
pp. 1094-1099
Author(s):  
Yuan Luo ◽  
Xue Qiang Tang
Keyword(s):  
Fractal Dimension ◽  
Wavelet Analysis ◽  
Image Binarization ◽  
Noise Background ◽  
Box Counting ◽  
Binarization Algorithm ◽  
Binarization Method

In MEMS parameter measure based on vision,the process of binarization is critical. In the situation of unbalancing illumination and noise background,the performance of traditional binarization method degrades. In this paper, a binarization method based on wavelet analysis and an optimal box counting (OBC) fractal dimension algorithm is proposed. At first,wavelet analysis is used to eliminate the effect of illumination distribution.Then the MEMS image binarization based on OBC reduces the effect of noise. Experiments show that, the method can get a considerable binarization result.

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