The weave pattern (texture) of woven fabric is considered to be an important factor of the design and production of high-quality fabric. Traditionally, the recognition of woven fabric has a lot of challenges due to its manual visual inspection. The approaches based on early machine learning algorithms directly depend on handcrafted features, which are time-consuming and occurs more errors. Hence, an automated system is needed for classification of woven fabric to improve productivity. Along with the rapid development of computer vision, the automatic and efficient methods for woven fabric classification are desperately needed. The prediction of fabric weave pattern Fabric is done by acquiring the high-quality images of the fabric. Then the acquired images are subjected to weave classification algorithm. The output of the processed image is used as an input to the Artificial Neural Network (ANN) which uses back propagation algorithm to calculate the weighted factors and generates the desired classification of weave patterns as an output. In this review paper discussed about the study on the various neural network that are used for prediction of fabric weave pattern.
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