Automated Defect Recognition Method by Using Digital Image Processing
نویسنده
چکیده
As existing infrastructure systems are aged and deteriorated rapidly, state agencies started searching for more advanced ways to maintain their valuable assets to the acceptable level. One of them is the application of digital image processing. Recently, in the civil engineering domain, digital image processing methods have been developed to the areas of pavement conditions, underground pipeline inspection, and steel bridge coating assessment (H. D. Cheng et al. 1999, S. K. Sinha et al. 2003, S. Lee et al. 2005). The main reasons to count on the advanced technology are due to such advantages as accuracy, objectivity, speed, and consistency. These distinct advantages have brought attention to state agencies to minimize the shortcomings of existing inspection practices. The conditions of steel bridge painting surfaces can be evaluated accurately and quickly by applying digital image processing. Also, machine vision-dependent inspections can provide more consistent inspection results than human visual inspections. Because conventional inspection heavily relies on individual abilities, inspection results are errorprone and may have wide variations between inspectors. The results can be different depending on personal preferences, work experiences, and the workload of the inspectors. It is pretty important to develop reliable infrastructure condition assessment for better maintenance of the assets. In case of bridge coating, bridge managers can more realistically develop long-term cost-effective maintenance programs if they have dependable coating condition data. Also, they can make decisions as to whether a bridge shall be painted again immediately or later. Efficient coating condition assessment is also essential for the successful implementation of steel bridge coating warranty contracting. Under the warranty contracting, an owner and a contractor inspect steel bridge coating conditions on a regular basis and decide whether additional maintenance actions are needed. However, it is extremely difficult to determine if a bridge contains more defects than an allowable level. If they are in conflict, they will go through a lengthy process to reach an agreement. This paper concerns with rust defects on highway steel bridges. Rust defects are one of the most commonly observed defects on coating surfaces and are to be taken care of appropriately since they can severely affect the structural integrity of bridges and generate unpleasant appearance to passing drivers. A rust defect assessment As existing infrastructure systems are aged and deteriorated rapidly, state agencies started searching for more advanced ways to maintain their valuable assets to the acceptable level. One of them is the application of digital image processing. Recently, in the civil engineering domain, digital image processing methods have been developed to the areas of pavement conditions, underground pipeline inspection, and steel bridge coating assessment. The main reasons to count on the advanced technology are due to such advantages as accuracy, objectivity, speed, and consistency. These distinct advantages have brought attention to state agencies to minimize the shortcomings of existing inspection practices. This paper deals with a digital image processing method to apply it to the evaluation of steel bridge coating conditions. Infrastructure condition assessment can be made more accurately and quickly with the aid of computerized processing system. The proposed method in this paper was designed to recognize the existence of bridge coating rust defects. It was developed by making pair-wise comparisons between a defective group and a non-defective group and generating eigenvalues to separate two groups. An automated defect recognition method can make a decision whether a given digitized image contains defects.
منابع مشابه
Identification of selected monogeneans using image processing, artificial neural network and K-nearest neighbor
Abstract Over the last two decades, improvements in developing computational tools made significant contributions to the classification of biological specimens` images to their correspondence species. These days, identification of biological species is much easier for taxonomist and even non-taxonomists due to the development of automated computer techniques and systems. In this study, we d...
متن کاملAutomated Rust Defect Recognition Method Based on Color and Texture Feature
Digital image processing has been applied to diverse industry disciplines. The wide application of digital image processing can be attributed to the following advantages: accuracy, objectivity, fastness, consistency, and the mixture of them. Although the RUst Defect Assessment(RUDA) method [1] was efficiently used to differentiate defective images from non-defective images on blue color coat, i...
متن کاملColor Image-Based Defect Detection Method for Bridge Coating Assessment
This paper presents a highly efficient method for recognizing the existence of bridge coating rust defects by using color image processing. The detection of defects on steel bridge surfaces during the operation and maintenance of bridge structures is important to ensure the safety and reliability of them. More advanced techniques such as digital image processing have been studied for better mon...
متن کاملDevelopment of Visual Inspection System Based on Vector Analysis Technique
The present paper proposes a new concept of image processing method based on vector representation for visual inspection test. The method was applied to detect defects and extract their profiles from digital 2D image of welded rough surface of the structures aiming at the development of automated visual inspection system. The potential availability of the new technique based on vector represent...
متن کاملDetection and Classification of Breast Cancer in Mammography Images Using Pattern Recognition Methods
Introduction: In this paper, a method is presented to classify the breast cancer masses according to new geometric features. Methods: After obtaining digital breast mammogram images from the digital database for screening mammography (DDSM), image preprocessing was performed. Then, by using image processing methods, an algorithm was developed for automatic extracting of masses from other norma...
متن کاملDetection and Classification of Breast Cancer in Mammography Images Using Pattern Recognition Methods
Introduction: In this paper, a method is presented to classify the breast cancer masses according to new geometric features. Methods: After obtaining digital breast mammogram images from the digital database for screening mammography (DDSM), image preprocessing was performed. Then, by using image processing methods, an algorithm was developed for automatic extracting of masses from other norma...
متن کامل