Kc. Fan et al., FABRIC CLASSIFICATION BASED ON RECOGNITION USING A NEURAL-NETWORK ANDDIMENSIONALITY REDUCTION, Textile research journal, 68(3), 1998, pp. 179-185
Fabric classification plays an important role in the textile industry.
In this paper, two fabric classification methods, the neural network
and dimensionality reduction, are proposed to automatically classify f
abrics based on measured hand properties. The methods are independent
and reinforce each other. The first method adopts a neural network to
recognize the category of an unknown fabric. In the second method, a d
imensionality reduction technique is applied to reduce the dimensional
ity of the measured properties of input fabrics from sixteen dimension
s to two. The reduced features are then plotted in a two-dimensional c
oordinate system to visualize and verify the classification results of
the neural network. In experiments conducted to verify the validity o
f our proposed approach, fabric data are expressed in the form of hand
properties extracted from the KES-FB system (Kawabata's evaluation sy
stem for fabrics). These experiments confirm the feasibility and effic
iency of our approach with a wide variety of fabrics.