Perceptual Grouping for Contour Extraction

This paper describes an algorithm that efficiently groups line segments into perceptually salient contours in complex images. A measure of affinity between pairs of lines is used to guide group formation and limit the branching factor of the contour search procedure. The extracted contours are ranked, and presented as a contour hierarchy. Our algorithm is able to extract salient contours in the presence of texture, clutter, and repetitive or ambiguous image structure. We show experimental results on a complex line-set. 1

Perimeter detection in sketched drawings of polyhedral shapes

Ponència presentada al STAG17: Smart tools and Applications in Graphics, celebrat a Catania (Itàlia) 11-12 setembre 2017This paper describes a new “envelope” approach for detecting object perimeters in line-drawings vectorised from sketches of polyhedral objects. Existing approaches for extracting contours from digital images are unsuitable for Sketch-Based Modelling, as they calculate where the contour is, but not which elements of the line-drawing belong to it. In our approach, the perimeter is described in terms of lines and junctions (including intersections and T-junctions) of the original line drawing

Auto-completion of contours in sketches, maps and sparse 2D images based on topological persistence.

We design a new fast algorithm to automatically complete closed contours in a finite point cloud on the plane. The only input can be a scanned map with almost closed curves, a hand-drawn artistic sketch or any sparse dotted image in 2D without any extra parameters. The output is a hierarchy of closed contours that have a long enough life span (persistence) in a sequence of nested neighborhoods of the input points. We prove theoretical guarantees when, for a given noisy sample of a graph in the plane, the output contours geometrically approximate the original contours in the unknown graph

A new sketch based interface using the gray-level co-occurrence matrix for perceptual simplification of paper based scribbles

The sketching activity has an important role in conceptual design and a variety of tools exist which help designers to facilitate the generation of 3D models form sketched drawings. This paper describes a new sketch-to-3D tool, which uses annotations to aid the interpretation of the drawing. Over-traced lines present in the designer’s scrib- bles provide an interpretation challenge, which must be resolved in order to obtain 3D models from these sketches. Perceptual grouping techniques used to interpret such images require that the drawing is represented as vectors. These are generally obtained through thinning or edge detection. However, we show that processing scribbles using these techniques result in a large number of vectors which do not provide a faithful representation of the drawing. This paper investigates the use of the co-occurrence matrix to perceptually simplify these drawings, thus obtaining a smaller number of vectors which describe the drawing more faithfully.peer-reviewe

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

Auto-completion of Contours in Sketches, Maps and Sparse 2D Images Based on Topological Persistence

We design a new fast algorithm to automatically complete closed contours in a finite point cloud on the plane. The only input can be a scanned map with almost closed curves, a hand-drawn artistic sketch or any sparse dotted image in 2D without any extra parameters. The output is a hierarchy of closed contours that have a long enough life span (persistence) in a sequence of nested neighborhoods of the input points. We prove theoretical guarantees when, for a given noisy sample of a graph in the plane, the output contours geometrically approximate the original contours in the unknown graph

A Dynamic Stroke Segmentation Technique for Sketched Symbol Recognition

In this paper, we address the problem of ink parsing, which tries to identify distinct symbols from a stream of pen strokes. An important task of this process is the segmentation of the users’ pen strokes into salient fragments based on geometric features. This process allows users to create a sketch symbol varying the number of pen strokes, obtaining a more natural drawing environment. The proposed sketch recognition technique is an extension of LR parsing techniques, and includes ink segmentation and context disambiguation. During the parsing process, the strokes are incrementally segmented by using a dynamic programming algorithm. The segmentation process is based on templates specified in the productions of the grammar specification from which the parser is automatically constructed

Identifying Perceptual Structures In Trademark Images

In this paper we focus on identifying image structures at different levels in figurative (trademark) images to allow higher level similarity between images to be inferred. To identify image structures at different levels, it is desirable to be able to achieve multiple views of an image at different scales and then extract perceptually-relevant shapes from the different views. The three aims of this work are: to generate multiple views of each image in a principled manner, to identify structures and shapes at different levels within images and to emulate the Gestalt principles to guide shape finding. The proposed integrated approach is able to meet all three aims