| Title |
The Recognition and Segmentation of the Road Surface State using Wavelet Image Processing |
| Authors |
Tae-Hwan Han ; Seung-Ki Ryu |
| Keywords |
Wavelet packet transform ; Polarization coefficient ; Time-frequency analysis ; Road surface condition ; Image recognition |
| Abstract |
This study focus on segmentation process that classifies road surfaces into 5 different categories, dry, wet, water, icy, and snowy surfaces by analyzing asphalt-paved road images taken in daylight By using the polarization coefficients, the proportions of horizontally polarized components to vertically polarized components, regions with over 1.3 polarization coefficients are classified as wet surfaces. Except for wet surfaces, the decision process applies time-frequency analysis to other parts by using the third order wavelet packet transform In addition, by using the average frequency characteristics of dry and icy surfaces from image templates, decide which is closer to a test image, and finally identify dry and icy surfaces. It is confirmed that the proposed estimation and segmentation of recognition on various images. This can be interpreted as an indication that image-only road surface condition supervision is probable. |