Automated Map Feature Vectorization with NOAA's Raster Nautical Chart
For this SBIR effort, first, we will prove that map features in NOAA's raster nautical charts can be extracted with automated means rather than manual digitizing. Second, we will prove that the extracted raster-based features can be vetorized with no or insignificant error in size, shape, and spacing among objects, yielding a robust raster/vector hybrid spatial database. Third, using a comparative analysis we will prove that while automatic feature extraction and vectorization can also be achieved by using a set of conventional image processing and GIS software, these ad hoc procedures are cumbersome, inefficient, ineffective, and error-prone as compared to the proposed SRE system that integrates automatic feature extraction, raster-to-vector conversion and vector-to-raster conversion into one unified information processing environment. For testing against the SRE system composed of the IMaG, Vectorize and Rasterizer, we will select XV, IDRISI, ENVI, ARC/INFO as its counterpart. The potential benefits will include savings in labor costs by a significant margin of up to 50 percent, and improved efficiency, effectiveness and accuracy in vector database generation.
Small Business Information at Submission:
Principal Investigator:J. Ching-yeng Huang
Susquehanna Resources And
84 Oak Street Binghamton, NY 13905
Number of Employees: