A Study On The Effects Of Noise Level, Cleaning Method, And Vectorization Software On The Quality Of Vector Data.
Al-Khaffaf, Hasan and Talib , Abdullah Zawawi and Abdul Salam, Rosalina (2007) A Study On The Effects Of Noise Level, Cleaning Method, And Vectorization Software On The Quality Of Vector Data. In: Proceedings of 7th International Workshop on Graphics Recognition – GREC 2007 (Proceedings of Extended Abstract and Online Proceedings)., 20-21 September 2007. , Curitiba, Brazil, .
In this paper we study different factors that affect vector quality. Noise level, cleaning method, and vectorization software are three factors that may influence the resulting vector data. Real scanned images from GREC'03 contest are used in the experiment. Three different levels of salt-and-pepper noise (5olo, l0%o, and l5o/o) are used. Noisy images are cleaned by six cleaning algorithms and then three different commercial raster to vector software are used to vectorize the cleaned images. vector Recovery Index (VRI) is the performance evaluation criteria used in this study to judge the quality of the resulting vectors compared to their ground truth data. Statistical analysis on the VRI values shows that vectorization software have the biggest influence on the quality of the resulting vectors.
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