§16§up with automated systems for assessment of road condition. For example, Haas et al (1997) developed an automated algorithm for detecting cracks and joints con- tion. Smith and Lin (1997) developed a fuzzy logic classification scheme for pavement distress condition. Oh et al (1997) developed iterative algorithm for overcoming noisy images of roads due to shadows and low light conditions. Koustsopoulos and Mishalani (1997) presented a model for distress assessment in a local (microscopic) and global (macroscopic) level using captured images of pavement. Lee (1993) presented a comparison between 15 different imaging al- rithms used in crack detection. Ground Penetration Radar (GPR) has also been used for pavement assessment. Special computer algorithms were developed for quick analysis of GPR data (Adeli 〓16§rol Currently imaging systems provide essential data for transportation and traffic engineering planning (Anon 1999). Machine vision techniques were introduced to intersection traffic signal control in the late 1970's (Chou and Sethi 1993). No- days, many systems have been developed all over the world for traffic analysis and control applications, in addition to image based systems for traffic violations. Nallamathu and Wang (1997) developed one of the first automated systems for license plate recognition using character recognition algorithm for the use in monitoring violators at toll stations and many other traffic applications. §04§to Transparent Soils.- Optical Techniques in Geotechnical Engineering.- to Light and Optics.- Optical Measurement of Strain and Stress.- Geotechnical Properties of Transparent Silica Powders.- Geotechnical Properties of Silica Gels.- Geotechnical Properties of Aquabeads.- Digital Image Correlation.- Application of DIC for Measuring Deformations in Transparent Soils.- Validation of Measured 2D Deformations.- 3D Deformation Measurement.- 2D Flow in Transparent Synthetic Soils.- Epilogue.
