Recently, deformable contour models have lately been used extensively for the detection and localization of boundaries for facilitating the image segmentation problem, and also for the extraction of man-made structures such as roads and buildings from gray level imagery. This study tackles the problem of embedding color image information, coming from different channels in deformable models of contour-type for the extraction and localization of road structures of small width that appear in color imagery mainly of R,G,B content and generally for supporting the verification and revision stages of the mapping process. More precisely, two models will be discussed together with their mathematical modeling and their implementational issues. One transforms the original R,G,B image content into color intensity and color contrast energy terms consisting of the external energy term which is formulated as a regularized-type function within the model which finally unevenly contributing to the radiometric content of the road structure. The other model is based on an optimization method that minimizes the given initial description of the road structure as the energy flow on the color edge field coming from the fusion of the R,G,B content. The solution is taken after reaching global minimum and determining the optimum 'color weighted path' executed in iterative fashion. In both the solution presents the contour, shifted and repositioned, expressing the centerline of the road structure which is localized in sub-pixel means taking into account the peculiarities and characteristics of certain spatial extent. Experimentation in semi-urban, in forested areas using medium scale imagery, and SPOT satellite images show the performance of the above models.