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Generative Art and Computer Vision: A Comprehensive Guide for Artists

Name: Generative Art and Computer Vision: A Comprehensive Guide for Artists
Author: James Parker
ISBN: 9798868821486

by James Parker

January 2026

Beginner to intermediate

445 pages

9h 37m

English

Apress

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Generative Art and Computer Vision
Table of Contents
About the Author
About the Technical Reviewer
1. Art, Vision, and Computers
Biological Vision SystemsElectronic Vision Systems – ImagesVisual ResponseBrightnessColorResolutionCoding and ImagesSet an Image to GreenDrawing ThingsLinesCirclesEllipsesRectanglesExamplesThe Drawing SurfaceRandomnessGenerative ArtAlgorithms in the ArtsGenerative Art DesignSummaryLibrary – Code Provided for You
2. Line
Drawing Vertical Lines Using PixelsDrawing General Straight Lines Using PixelsThe DDA Algorithm for Drawing LinesOther Forms of Straight LineDashed linesThick LinesJagged LinesTextured LinesLines of Variable ThicknessCurved LinesArcsConnecting ArcsGeneral Curves - SplinesExample: A VaseSimulating Human Drawn LinesIdentifying Lines – Vision or “Undrawing”Brute Force – Tracing LinesExtracting Curves from PixelsThick and Thin Lines (Again)What Use Is This?SummaryTools and ExamplesLibrary – Code provided for you
3. Value
Pixel ValuesThe Gray-Level HistogramExample: ContouringContrastBrightening and Contrast ExpansionHistogram EqualizationHistogram SpecificationThresholdingThresholding: Select a ValueUsing the MeanUsing the Gray-Level HistogramTwo Pixel ClassesLocal ThresholdsRegions and BoundariesSmoothingMean and MedianBoundariesEdgesSobel EdgesCanny EdgesShadingBi-Level Display of ValuesHalftonesDitheringQuantization: Changing Number of LevelsMarilynFilled ContoursSummaryTools and ExamplesLibrary Code
4. Color
Color RepresentationsHue, Saturation, and BrightnessPaint and Subtractive MixingThe RYB Color ModelConverting RGB to RYBMixingThe CMYK Color ModelMunsellMunsell Digital ToolColor from ValuePseudocolor (False Color)Space ImagesColorizationColor TemperatureVariations on a ColorTintsShadesTonesColor PairingsComplementary ColorsSplit Complementary ColorsTriadic ColorsAnalogousTransparencyRestricting the Number of Colors (Quantization Again)Equal Distance Between ColorsMedian CutSmoothingColor and EdgesColor PsychologyFinding Color RegionsExample: Orange TreeExample: Sepia ToningSummaryTools and ExamplesLibrary Code
5. Shape
Geometric ShapesPolygonsCirclesEllipses and OvalsShapes – Closed CurvesOrganic ShapesExample – BlobsExample: Spatter or SplatExample – Natural Organic ShapesExample – Invented Shapes (Midcentury Modern)Drawing the N-FlowerThe Zoop PoleDrawing A ZoopThe PoleIdentifying PatternsExtracting Shapes from ImagesUsing Features of ShapesFeatures That Are Scale DependentAreaPerimeterLength and WidthFeatures That Are Scale IndependentCircularityRectangularitySignaturesConvexityConvex HullConvex Area and Convex PerimeterConvex DeficienciesTemplate MatchingExample: GhostsSummaryLibrary Code
6. Texture
Applying TexturesTraditional Texture MappingNatural TexturesTiled TexturesReflectionGIMPSynthetic TexturesControlled Randomness – Value NoiseCubic NoiseControlled Randomness – Perlin NoiseShadingUsing CharactersGrunge TexturesIdentifying TexturesLocal Binary PatternsSummaryLibrary code

7. Form
Coordinates in 3DCoordinate SystemsShapes in Object CoordinatesThe Digital Perspective Transform: What Do We Need?Changing ViewpointDrawing a Cube – Using ProcessingDrawing Basic ObjectsMore Complex 3D ObjectsThe Most Basic Perspective ProjectionOne-Point PerspectiveOne Point Perspective and Computer GraphicsGeometric Transforms in 3DTranslationScaleRotationRotation About the Object CenterParallel Coordinate ProjectionsOrthographicFinding the Vanishing Point in an Image3D ViewingDisparityImage PairsAnaglyphsTextures in 3DMaking a BuildingTexture Mapping Triangles3D Models.OBJ FilesIllumination ModelsAmbient LightDiffuse ReflectionFlat ShadingGouraud ShadingExample: CubismSummaryLibrary CodeStand-Alone Demo Programs
8. Space
Empty CanvasPositive and Negative SpaceThree-Dimensional SpaceDeep and Shallow SpaceDigital Image SpaceDigital Image Space is InaccurateDigital Images Are Distorted for ConvenienceDigital Image Space Is MalleableDigital Image Space Is RelativeDigital Image Space Can Be ImaginaryThe Example of a TesseractDigital Image Space Is Outside of TimeSpace and Vision – The Rendering ProcessVisual ResponseSpace in Abstract CompositionCruciform CompositionAsymmetrical or Unbalanced CompositionHorizontal Composition: High and LowVertical CompositionOverlapping FramesCurvilinear CompositionConstellation or Group Mass CompositionDiagonal CompositionGolden Section or Golden RatioCentered CompositionRadiant or Radiating CompositionBalanced Composition3-Spot or Triangular CompositionTunnel CompositionL or Rectangular CompositionPattern CompositionO or Circular CompositionS or Compound Curve CompositionCompositional Rules That Make SenseSummaryLibrary Code
9. Dynamism
AnimationTimeFrame-by-Frame AnimationCreating Animation FramesStraight Ahead AnimationKey Frame AnimationRotoscopingProcedural AnimationChroma-KeyResponsive ArtColorSpeedShapeVideo CamerasSummaryStand-alone Demo Programs
Appendix I: Math for Generative Art
Most Important: Essential TrigonometryAnalytic Geometry – LinesInterpolationSummary
Appendix II: Programming in Processing
Numbers and VariablesColorStatementsGroups/BlocksIF StatementWHILE StatementFOR StatementArraysImagesFunctionsStatic vs. Dynamic Processing ProgramsAn Art Example
References
Chapter 1Chapter 2Chapter 3Chapter 4Chapter 5Chapter 6Chapter 7Chapter 8Chapter 9Appendix II
Index

Content preview from Generative Art and Computer Vision: A Comprehensive Guide for Artists

J. ParkerGenerative Art and Computer Visionhttps://doi.org/10.1007/979-8-8688-2148-6_1

1. Art, Vision, and Computers

James Parker¹

(1)

Rockyview County, AB, Canada

It seems obvious that to be a visual artist, one should be able to see. But what does that really mean? Seeing is more than simply detecting light or being able to form images on a film or retina or computer chip. Seeing is about being able to use images to make decisions or draw conclusions. For that to happen, we have to be able to discern shapes and objects in an image. An object is something that we have a label for, and so we must not only have encountered it previously, but we must be able ...

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Generative Art and Computer Vision: A Comprehensive Guide for Artists

by James Parker

1. Art, Vision, and Computers

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.