Haptic Modeling of textile has attracted significant interest over the last decade. In spite of extensive research, no generic
system has been proposed. The previous work mainly assumes that textile has a 2D planar structure. They also require
time-consuming measurement of textile properties in construction of the mechanical model. A novel approach for haptic
modeling of textile is proposed to overcome the existing shortcomings. The method is generic, assumes a 3D structure
for the textile, and deploys computational intelligence to estimate the mechanical properties of textile. The approach is
designed primarily for display of textile artifacts in museums. The haptic model is constructed by superimposing the
mechanical model of textile over its geometrical model. Digital image processing is applied to the still image of textile to
identify its pattern and structure through a fuzzy rule-base algorithm. The 3D geometric model of the artifact is
automatically generated in VRML based on the identified pattern and structure obtained from the textile image. Selected
mechanical properties of the textile are estimated by an artificial neural network; deploying the textile geometric
characteristics and yarn properties as inputs. The estimated mechanical properties are then deployed in the construction
of the textile mechanical model. The proposed system is introduced and the developed algorithms are described. The
validation of method indicates the feasibility of the approach and its superiority to other haptic modeling algorithms.
Geometric modeling and haptic rendering of textile has attracted significant interest over the last decade. A haptic representation is created by adding the physical properties of an object to its geometric configuration. While research has been conducted into geometric modeling of fabric, current systems require time-consuming manual recognition of textile specifications and data entry. The development of a generic approach for construction of the 3D geometric model of a woven textile is pursued in this work. The geometric model would be superimposed by a haptic model in the future work. The focus at this stage is on hand-woven textile artifacts for display in museums. A fuzzy rule based algorithm is applied to the still images of the artifacts to generate the 3D model. The derived model is exported as a 3D VRML model of the textile for visual representation and haptic rendering. An overview of the approach is provided and the developed algorithm is described. The approach is validated by applying the algorithm to different textile samples and comparing the produced models with the actual structure and pattern of the samples.