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no binarization algorithm is best for all types of images, we also give the results of the proposed method applied to historical documents.

Evaluation of New In-Ditch Methods for Measurement and Assessment of External Corrosion

2014 ◽  
Author(s):  
Pablo Cazenave ◽  
Katina Tiñacos ◽  
Ming Gao ◽  
Richard Kania ◽  
Rick Wang
Keyword(s):  
New Technologies ◽  
3D Scanning ◽  
Primary Objective ◽  
Scanning System ◽  
Calculation Methods ◽  
Integrity Assessment ◽  
External Corrosion ◽  
Non Destructive ◽  
Scanning Systems ◽  
Inspection Performance

New technologies for in-ditch non-destructive evaluation were lately developed and are becoming of mainstream use in the evaluation of external corrosion features for both In-Line-Inspection performance evaluation and pipeline integrity assessment. However, doubt was cast about the reliability and repeatability of these new technologies (hardware and processing software) when compared with those used in the traditional external-corrosion in-ditch measurement and the reliability of the pipeline integrity assessment calculations (PBurst) embedded in their software when compared with industry-wide accepted calculation methods. Therefore, the primary objective of this study is to evaluate the variation and repeatability of the measurements produced by these new technologies in corrosion feature profiling and associated PBurst calculations. Two new 3D scanning systems were used for the evaluation of two pipe samples removed from service which contain complex external corrosion features in laboratory. The reliability of the 3D scanning system in measuring corrosion profiles was evaluated against traditional profile gage data. In addition, the associated burst pressures reported by the systems were compared with results obtained using industry-widely used calculation methods. Also, consistencies, errors and gaps in results were identified. In this paper, the approach used for this study is described first, the evaluation results are then presented and finally the findings and their implications are discussed.

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.

scholarly journals A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1128
Author(s):  
Chern-Sheng Lin ◽  
Yu-Ching Pan ◽  
Yu-Xin Kuo ◽  
Ching-Kun Chen ◽  
Chuen-Lin Tien
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Color Space ◽  
Color Difference ◽  
Color Space Conversion ◽  
Before And After ◽  
Artificial Intelligence Technology ◽  
Artificial Intelligence Algorithm ◽  
Time Image ◽  
Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

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