A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
International Journal of Computer Vision
Sketches with Curvature: The Curve Indicator Random Field and Markov Processes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Perceptually Closed Paths in Sketches and Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptually-supported image editing of text and graphics
Proceedings of the 16th annual ACM symposium on User interface software and technology
Resolving ambiguities to create a natural computer-based sketching environment
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Sketch interpretation and refinement using statistical models
EGSR'04 Proceedings of the Fifteenth Eurographics conference on Rendering Techniques
Paintbrush rendering of lines using HMMs
GRAPHITE '05 Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Stroke extraction and classification for mesh inflation
Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium
Technical Section: SpeedSeg: A technique for segmenting pen strokes using pen speed
Computers and Graphics
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This paper presents a smart interface that automatically extracts and refines pen strokes from images of hand drawn sketches. The interface allows users to digitize hand-drawn material such sketches of flowcharts, cartoons or other pen based drawings and automatically isolate and refine the individual strokes making up the sketch. First, we present a method for extracting pen strokes based on learned constraints on curves. The approach consists of using a training set that shows good examples of curves and how a user would draw them. Given an image of a hand-drawn sketch, the system selects the pen stroke that is most statistically consistent with the examples in the training set and ranks the others based on their likelihood. Users can keep the selected candidate or they may scroll through the other top candidates to select a preferred solution. Second, we present an overview of our refinement procedure and its application on the extracted pen strokes. Using the same database of examples, the extracted pen stroke is refined to make it 'look' more like those in the database.