Algorithmic Perception of Vertices in Sketched Drawings of Polyhedral Shapes

In this article, visual perception principles were used to build an artificial perception model aimed at developing an algorithm for detecting junctions in line drawings of polyhedral objects that are vectorized from hand-drawn sketches. The detection is performed in two dimensions (2D), before any 3D model is available and minimal information about the shape depicted by the sketch is used. The goal of this approach is to not only detect junctions in careful sketches created by skilled engineers and designers but also detect junctions when skilled people draw casually to quickly convey rough ideas. Current approaches for extracting junctions from digital images are mostly incomplete, as they simply merge endpoints that are near each other, thus ignoring the fact that different vertices may be represented by different (but close) junctions and that the endpoints of lines that depict edges that share a common vertex may not necessarily be close to each other, particularly in quickly sketched drawings. We describe and validate a new algorithm that uses these perceptual findings to merge tips of line segments into 2D junctions that are assumed to depict 3D vertices

A structural representation for understanding line-drawing images

International audienceIn this paper, we are concerned with the problem of finding a good and homogeneous representation to encode line-drawing documents (which may be handwritten). We propose a method in which the problems induced by a first-step skeletonization have been avoided. First, we vectorize the image, to get a fine description of the drawing, using only vectors and quadrilateral primitives. A structural graph is built with the primitives extracted from the initial line-drawing image. The objective is to manage attributes relative to elementary objects so as to provide a description of the spatial relationships (inclusion, junction, intersection, etc.) that exist between the graphics in the images. This is done with a representation that provides a global vision of the drawings. The capacity of the representation to evolve and to carry highly semantic information is also highlighted. Finally, we show how an architecture using this structural representation and a mechanism of perceptive cycles can lead to a high-quality interpretation of line drawings

Line tracking algorithm for scribbled drawings

This paper describes a line tracking algorithm that may be used to extract lines from paper based scribbles. The proposed algorithm improves the performance of existing sparse-pixel line tracking techniques that are used in vectorization by introducing perceptual saliency and Kalman filtering concepts to the line tracking. Furthermore, an adaptive sampling size is used such that it is possible to adjust the size of the tracking step to reflect the stroke curvature.peer-reviewe

Automatic Structural Scene Digitalization

In this paper, we present an automatic system for the analysis and labeling of structural scenes, floor plan drawings in Computer-aided Design (CAD) format. The proposed system applies a fusion strategy to detect and recognize various components of CAD floor plans, such as walls, doors, windows and other ambiguous assets. Technically, a general rule-based filter parsing method is fist adopted to extract effective information from the original floor plan. Then, an image-processing based recovery method is employed to correct information extracted in the first step. Our proposed method is fully automatic and real-time. Such analysis system provides high accuracy and is also evaluated on a public website that, on average, archives more than ten thousands effective uses per day and reaches a relatively high satisfaction rate.Comment: paper submitted to PloS On

Scribbles to vectors : preparation of scribble drawings for CAD interpretation

This paper describes the work carried out on off-line paper based scribbles such that they can be incorporated into a sketch-based interface without forcing designers to change their natural drawing habits. In this work, the scribbled drawings are converted into a vectorial format which can be recognized by a CAD system. This is achieved by using pattern analysis techniques, namely the Gabor filter to simplify the scribbled drawing. Vector line are then extracted from the resulting drawing by means of Kalman filtering.peer-reviewe

A complete hand-drawn sketch vectorization framework

Vectorizing hand-drawn sketches is a challenging task, which is of paramount importance for creating CAD vectorized versions for the fashion and creative workflows. This paper proposes a complete framework that automatically transforms noisy and complex hand-drawn sketches with different stroke types in a precise, reliable and highly-simplified vectorized model. The proposed framework includes a novel line extraction algorithm based on a multi-resolution application of Pearson's cross correlation and a new unbiased thinning algorithm that can get rid of scribbles and variable-width strokes to obtain clean 1-pixel lines. Other contributions include variants of pruning, merging and edge linking procedures to post-process the obtained paths. Finally, a modification of the original Schneider's vectorization algorithm is designed to obtain fewer control points in the resulting Bezier splines. All the proposed steps of the framework have been extensively tested and compared with state-of-the-art algorithms, showing (both qualitatively and quantitatively) its outperformance

Analysis of Digital Logic Schematics Using Image Recognition

This thesis presents the results of research in the area of automated recognition of digital logic schematics. The adaptation of a number of existing image processing techniques for use with this kind of image is discussed, and the concept of using sets of tokens to represent the overall drawing i s explained in detail. Methods are given for using tokens to describe schematic component shapes, to represent the connections between components, and to provide sufficient information to a parser so that an equation can be generated. A Microsoft Windows-based test program which runs under Windows 95 or Windows NT has been written to implement the ideas presented. This program accepts either scanned images of digital schematics, or computer-generated images in Microsoft Windows bitmap format as input. It analyzes the input schematic image for content, and produces a corresponding logical equation as output. It also provides the functionality necessary to build and maintain an image token library

Scribble vectorization using concentric sampling circles

In this paper we introduce a path extraction algorithm for multi-stroke scribbled paths by making use of path-centred concentric sampling circles. Circle and line geometry is then exploited to efficiently obtain piece-wise linear models of the multi-stroke segments in the drawing. Parzen-window estimation is used to obtain the probability distribution of the grey-level profile of the sampling circles to determine the intersecting angle of the sampling circle with the stroke segments and hence determine the line model parameters. The results obtained show that the algorithm identifies the line models accurately while reducing considerably the computational time required to obtain the line models.peer-reviewe