The micro and small garment industries use traditional molds based on drawings on paper for the cutting of the fabric. This process is performed manually at the discretion of the operator, generating material loss during the cutting process. To make this task more efficient and reduce losses, this paper presents a technique for editing and vectorization of physical molds using digital image processing techniques, allowing the edition, modification or multiplication of the selected mold. For this purpose, a simple, low-cost device was developed to take photographs of the molds and an automatic method for contour detection and vectorization of textile molds was realized. Three edge detection methods, Sobel, Canny - Deriche and morphological gradient, were compared. Then, the Harris corner detection method was used, achieving a better detection, reducing the number of false corners, by using the image in gray levels as the input of the detector. The shapes of the contours between the corners were approximated by cubic splines, obtaining an analytical representation of each mold, being used to manipulate the size and position to place it in a better way on the fabric, achieving a significant reduction in fabric losses. The developed low-cost application thus allows the approximation of the models by vectorial representation, allowing their manipulation in an easy way and with a low consumption of computational resources without losing important information of the molds. The molds can thus be moved, rotated and scaled to accommodate them within the available fabric space.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.