University of Tabriz Journal of Civil and Environmental Engineering 2008-7918 55 120 2025 10 23 Comparative Analysis of Wavelet Decomposition Levels in Order to Full-Automated Classification of Asphalt Pavement Distresses Texture Comparative Analysis of Wavelet Decomposition Levels in Order to Full-Automated Classification of Asphalt Pavement Distresses Texture 1 13 14674 10.22034/jcee.2022.46583.2044 FA Reza Shahabian Moghaddam Civil Engineering Dept. ; Engineering Faculty; Ferdowsi University of Mashhad, Iran Seyad Ali Sahaf Civil Engineering Dept. ; Engineering Faculty; Ferdowsi University of Mashhad, Iran Abolfazl Mohammadzadeh Moghaddam Civil Engineering Dept. ; Engineering Faculty; Ferdowsi University of Mashhad, Iran Journal Article 2021 06 17 Evaluation of the pavement performance plays a vital role in Pavement Management System (PMS). Identification of road surface failures (pavement distresses) is of the main elements in the process of pavement evaluation at the network and project level road assessment. The simplest method of pavement distress evaluation is visual inspection and rating of apparent condition of the road surface by experts. This approach of pavement evaluation not only increases the cost and time of inspection operations, but also depends on the personal judgment (subjective) of assessors and brings about non-repeatable results. Furthermore, it exposes the inspectors to unsafe working situations on highways. In the last decade, extensive researches have been conducted for the development of semi-automated and fully-automated methods of pavement condition evaluation to overcome the deficiencies and problems related to manual and visual evaluation of pavement distresses. Although some standards and protocols such as AASHTO R 55-10 have been developed in accordance with automatic distress data collection conditions, limited success has been achieved in recognition and classification of different pavement distresses. This can be attributed to severe disorders and irregularities of distress patterns, especially in asphalt pavements. Additionally, most of the current automatic evaluation systems are associated with heavy computational loads due to employing complex algorithms and they mainly focus on automatic detection and classification of pavement cracks. It should be noted that cracks only represent one important aspect of pavement distresses. Other types of distresses such as potholes, patching, bleeding and raveling also play an important role in the decline of pavement quality index and affect the treatments and maintenance options proposed by PMS. Considering these limitations, the authors employed a method with superior precision and efficiency to identify and process pavement distresses. Evaluation of the pavement performance plays a vital role in Pavement Management System (PMS). Identification of road surface failures (pavement distresses) is of the main elements in the process of pavement evaluation at the network and project level road assessment. The simplest method of pavement distress evaluation is visual inspection and rating of apparent condition of the road surface by experts. This approach of pavement evaluation not only increases the cost and time of inspection operations, but also depends on the personal judgment (subjective) of assessors and brings about non-repeatable results. Furthermore, it exposes the inspectors to unsafe working situations on highways. In the last decade, extensive researches have been conducted for the development of semi-automated and fully-automated methods of pavement condition evaluation to overcome the deficiencies and problems related to manual and visual evaluation of pavement distresses. Although some standards and protocols such as AASHTO R 55-10 have been developed in accordance with automatic distress data collection conditions, limited success has been achieved in recognition and classification of different pavement distresses. This can be attributed to severe disorders and irregularities of distress patterns, especially in asphalt pavements. Additionally, most of the current automatic evaluation systems are associated with heavy computational loads due to employing complex algorithms and they mainly focus on automatic detection and classification of pavement cracks. It should be noted that cracks only represent one important aspect of pavement distresses. Other types of distresses such as potholes, patching, bleeding and raveling also play an important role in the decline of pavement quality index and affect the treatments and maintenance options proposed by PMS. Considering these limitations, the authors employed a method with superior precision and efficiency to identify and process pavement distresses. https://ceej.tabrizu.ac.ir/article_14674_e87cc7c28f7301ca2c48169b86931e4c.pdf