Silhouette shape and detail texture based garment style recognition

Author

Qian, Suqin ; Jiang, Lifeng ; Dong, Aihua

Author_Institution

Dept of Inst. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China

Volume

2

fYear

2011

fDate

10-12 June 2011

Firstpage

441

Lastpage

445

Abstract

Garment style is closely related to silhouette shape and detail shape. This paper proposes image processing technology to separate the silhouette curve of the garment and obtain the image representing the drape pleating shadow. Firstly, 13 descriptors representing the shape characteristics and detail texture are acquired. After that, a three layer BP neural network is employed to recognition the garment style. Finally, the proposed method is verified in the skirt style classification and the experimental result shows the effective of the method.

Keywords

backpropagation; clothing; clothing industry; image classification; image representation; image texture; neural nets; production engineering computing; backpropagation neural network; detail texture; drape pleating shadow; garment style recognition; image processing technology; image representation; silhouette shape; skirt style classification; Artificial neural networks; Clothing; Fabrics; Image edge detection; Mathematical model; Pixel; Shape; BP Neural Network; Detail Texture; Garment Modeling; Image Segmentation; Silhouette Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-8727-1

Type

conf

DOI

10.1109/CSAE.2011.5952504

Filename

5952504