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

Jon SchendtUniversity of Wisconsin-Platteville

Image Processing – A Computational Approach

OutlineOverview of Image ProcessingBit Operations (Boolean Logic)Chain, Crack, and Run CodesNoise Filtering and ReductionAnti-AliasingDitheringApplicationsDemonstration

Overview of Image Processing


Bit Operations (Boolean Logic)AND

Used for color filtering, as well as boolean noise reduction

ORUsed primarily to apply color filters

XORUsed to flip bits. Great for inverse algorithms


Chain, Crack, and Run CodesBuilt on the fact that all images have

“edges”Used in pattern-matchingNeeds to distinguish between background

data and foreground data

Chain CodesBuilt on the presumption that images are

digitalized, and have ‘Edges’Distinguish from foreground and

background

Chain Codes

Chain Codes {5,6,7,7}

Crack CodesSimilar to chain codes, but with fewer

possibilitiesLeads to possible “cracks” in the code

Crack Codes {3,2,3,3,0,3,0,0}.

Run CodesGreat for brute-force pattern recognitionAnalyzes pixels, and creates rows based on

parameters


Noise Filtering and ReductionSUSAN

Weighting PixelsPreserves Edges, colors, while reducing overall noise

Overall AlgorithmUses the weighting pixels algorithm to determine

which color should be prominentCreates an image that is almost always free of

scatter noise, while preserving quality and sharpness (no blurs)

Qualitative results of the SUSAN algorithm

Qualitative results of the SUSAN algorithm


Anti-AliasingWorks by creating a blur on objectsGives a “far away” look


DitheringOnly necessary on computers with a small color palateMaking intermediary colors through small pixels


ApplicationsGames

2-D Games3-D Games

MedicalDetecting tumorsCT Scan analysisAutomated devices

Applications cont.Military

DARPARADAR tools

CorporateAutonomous robotsPattern-matching software

EducationalMachine Sight


Documents

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