In the present paper, we propose an automatic snapping method that aligns fuzzy objects in a multi-resolution grid system in order to improve the efficiency of sketch-based CAD systems. The sketch-based CAD system that we have previously realized successfully identifies sketch drawings as primitive geometrical curve objects by treating the sketches as fuzzy objects, the fuzziness of which is associated with the roughness of the drawing manner. However, when the system aligns the identified objects with a grid system, difficulties in the grid resolution setting arise because the identified objects often consist of both fine and coarse portions and thus require different grid resolution settings for proper alignment. Meanwhile, the resolution problem with respect to cursor point snapping has been solved by multi-resolution fuzzy grid snapping (MFGS), which realizes automatic selection of the snapping resolution by treating the cursor as a fuzzy point, the fuzziness of which is associated with the roughness of the pointing manner of the user. The present paper proposes a method to apply MFGS to fuzzy objects in order to resolve the difficulties involved in the setting of the snapping resolution of the sketch-based CAD system. Experimental results show that users can align identified objects to an appropriate resolution through MFGS by controlling the roughness of the drawing manner.
This paper presents a grid snapping technique, called multi-resolution fuzzy grid snapping (MFGS), that enables automatic mouse cursor snapping for a multi-resolution grid system. Quick and frequent switching between high-and low-resolution grid snapping is essential to make geometrical drawings that include both fine and coarse structures when using CAD systems with ordinary single-resolution grid systems. MFGS is intended to relieve users of this tedious manual switching. MFGS dynamically selects an appropriate snapping resolution level from a multi-resolution grid system according to the pointing behavior of the user. MFGS even supports an extremely fine grid resolution level, which is referred to as the nosnapping level. We show experimental results which demonstrate that MFGS is an effective grid snapping technique that speeds up low-resolution grid snapping while retaining the ability to snap to high-resolution grids. Furthermore, we examine the role of fuzziness in MFGS and its effect on snapping performance.
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