Web-based clothing searcher utilizing convolutional neural networks and dissimilarity rules for color classification in the HSL color space and ORB algorithm for garment characterization

This study proposes a methodology for searching for clothing on the web using convolutional neural networks (CNN) and a color obtaining module. The system is based on the creation of a color base in the HSL (Hue, Saturation, Luminosity) space. It determines the color of an image based on dissimilarity rules. The base image, previously processed by a CNN, along with the result of obtaining the color, generates a string of characters. This string is entered into a search engine, resulting in garments that resemble the base image. These garments are processed with the ORB algorithm to extract their features and compare them with those of the base image. In this way, it can be determined which of the garments is most like the base image. This work offers new perspectives and useful techniques for obtaining colors, significantly improving the accuracy and efficiency of object search on the web.