Jon Schendt University of Wisconsin-Platteville Image Processing – A Computational Approach.

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Presentation transcript:

Jon Schendt University of Wisconsin-Platteville Image Processing – A Computational Approach

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration

Overview of Image Processing

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration

Bit Operations (Boolean Logic) AND Used for color filtering, as well as boolean noise reduction OR Used primarily to apply color filters XOR Used to flip bits. Great for inverse algorithms

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration

Chain, Crack, and Run Codes Built on the fact that all images have “edges” Used in pattern-matching Needs to distinguish between background data and foreground data

Chain Codes Built on the presumption that images are digitalized, and have ‘Edges’ Distinguish from foreground and background

Chain Codes Chain Codes  {5,6,7,7}

Crack Codes Similar to chain codes, but with fewer possibilities Leads to possible “cracks” in the code Crack Codes  {3,2,3,3,0,3,0,0}.

Run Codes Great for brute-force pattern recognition Analyzes pixels, and creates rows based on parameters

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration

Noise Filtering and Reduction SUSAN Weighting Pixels Preserves Edges, colors, while reducing overall noise Overall Algorithm Uses the weighting pixels algorithm to determine which color should be prominent Creates an image that is almost always free of scatter noise, while preserving quality and sharpness (no blurs)

Qualitative results of the SUSAN algorithm

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration

Anti-Aliasing Works by creating a blur on objects Gives a “far away” look

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration

Dithering Only necessary on computers with a small color palate Making intermediary colors through small pixels

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration

Applications Games 2-D Games 3-D Games Medical Detecting tumors CT Scan analysis Automated devices

Applications cont. Military DARPA RADAR tools Corporate Autonomous robots Pattern-matching software Educational Machine Sight

Outline Overview of Image Processing Bit Operations (Boolean Logic) Chain, Crack, and Run Codes Noise Filtering and Reduction Anti-Aliasing Dithering Applications Demonstration