Hector Santos Rosario MKS Instruments, Inc. (United States) Eli Saber Rochester Institute of Technology (United States) Wencheng Wu Xerox Corp. (United States) Kartheek Chandu Rochester Institute of Technology (United States)
We describe a method for automatically detecting streaks in printed images using adaptive window-based image projections and mutual information. The proposed approach accepts a scanned image enclosing the defect and computes the projections across the entire image at different window sizes. The resulting traces collected from the projections are analyzed with a peak detection algorithm and subsequently correlated using normalized mutual information to pinpoint the location and width of streak(s). Finally, for a given peak, the window size is changed adaptively to identify and locate the intensity and length of the corresponding streak(s) while maximizing the signal-to-noise ratio. Results on synthetic and real-life images are provided to demonstrate the effectiveness of our proposed technique.