Utilizing Scalable Vector Graphics and Algorithms for Creative Coding and Design Matthew, David. creator author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text xxu 2024 1st ed. 2024. monographic eng

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access XXIV, 257 p. 73 illus., 67 illus. in color. online resource. This book introduces you to the exciting world of generative art and creative coding through the medium of JavaScript and Scalable Vector Graphics (SVG). Using tried and trusted techniques, you’ll tackle core topics such as randomness and regularity, noise and naturalistic variance, shape and path creation, filter effects, animation, and interactivity. In the process you’ll learn SvJs, a JavaScript library that closely mirrors the SVG spec and makes scripting SVG intuitive and enjoyable. You’ll also study the craft of generative art and its creative process, along with JavaScript fundamentals, using modern ES6+ syntax. Each chapter will build upon the previous one, and those completely new to programming will be given a primer to help them find their feet. Generative Art with JavaScript and SVG will take you on a fun journey, peppered with plenty of sketches throughout, designed not only to explain, but to inspire. You Will: • Structure and randomise compositions. • Understand the different types of randomness and their probability distributions. • Create organic variance with the SvJs Noise module. • Apply SVG filter effects in a generative fashion. • Explore different approaches to animating with SVG. • Make your compositions dynamic and interactive. 1. The Beginner’s Path -- 2. A Programming Primer -- 3. All About SVG -- 4. Randomness and Regularity -- 5. The Need for Noise -- 6. The All-Powerful Path -- 7. Motion and Interactivity -- 8. Filter Effects -- 9. The Generative Way. by David Matthew. Internet programming Graphic arts User interfaces (Computer systems) Human-computer interaction Image processing Digital techniques Computer vision Web Development Graphic Design User Interfaces and Human Computer Interaction Computer Imaging, Vision, Pattern Recognition and Graphics QA76.625 9798868800863 https://doi.org/10.1007/979-8-8688-0086-3 https://doi.org/10.1007/979-8-8688-0086-3 240322 20251030111739.0 979-8-8688-0086-3