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.