Title :
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
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;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
DOI :
10.1109/CSAE.2011.5952504