Image‐Based Expert‐System Approach to Distress Detection on CRC Pavement-Reference-Cited by-同舟云学术

Image‐Based Expert‐System Approach to Distress Detection on CRC Pavement

Published:1994-01 Issue:1 Volume:120 Page:52-64
ISSN:0733-947X
Container-title:Journal of Transportation Engineering
language:en
Short-container-title:J. Transp. Eng.

Author:

Tsao Stephen¹,Kehtarnavaz Nasser²,Chan Paul³,Lytton Robert⁴

Affiliation:

1. Res. Asst., Texas Transp. Inst. (TTI), Texas A&M Univ., College Station, TX 77843

2. Assoc. Prof., Dept. of Electrical Engrg., Texas A&M Univ., College Station, TX

3. Engrg. Res. Assoc., Texas Transp. Inst. (TTI), Texas A&M Univ., College Station, TX

4. A.P. & Florence Wiley Chair Prof., Dept. of Civ. Engrg., Texas A&M Univ., College Station, TX

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-947X%281994%29120%3A1%2852%29

Reference12 articles.

1. CLIPS reference manual Version 4.2. (1989). NASA Artificial Intelligence Section Houston Tex.

2. Copp R. (1990). “Field test of three video distress recognition systems—Pavedex Inc. VideoComp Roadman‐PCES.” Automated Pavement Distress Data Recognition Seminar Iowa State Univ. Press 239–257.

3. Giarratano J. (1989). Expert systems: principles and programming . PWS‐KENT Boston Mass.

4. Gonzalez R. and Wintz P. (1987). Digital image processing . Addison‐Wesley North Reading Mass.

5. Haas C. Shen H. Phang W. A. and Haas R. (1985). “An expert system for automation of pavement condition inventory data.” Proc. North American Pavement Management Conf. Toronto Canada.

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