DIGITAL IMAGE PROCESSING SYSTEM FOR THE RECOGNITION AND ASSOCIATION OF PATTERNS IN THE MANAGEMENT INVENTORY IN FOOTWEAR
Digital image processing system to manage inventories
DOI:
https://doi.org/10.33110/inceptum.v17i32.420Keywords:
: Pearson correlation coefficient, Inventory management, digital image processing, pattern recognition.Abstract
The objective of this project is to identify by means of artificial intelligence the degree of similarity or difference between images of footwear, digital image processing and pattern recognition techniques are used to identify matches and link them to the stocks available in a finished product warehouse, in order to efficiently manage inventories. Different digital processing techniques were used in MATLAB (Matrix Laboratory) such as: binary image, intensity image, masks to detect edges, to compare patterns using the Pearson correlation coefficient, as a result a system capable of identifying morphological differences between models, views and colors is obtained, associating them with a database. A user interface was generated that allows to process a footwear model through a digital image and identify the existing quantities in the physical inventory by size and display them on the screen.
Downloads
Downloads
Published
Versions
- 2023-01-19 (2)
- 2023-01-18 (1)
How to Cite
Issue
Section
License
Copyright (c) 2023 INCEPTUM
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All contributions made to INCEPTUM Revista de Investigación en Ciencias de la Administración are published and distributed under an International Public License - CC BY-NC-ND 4.0 (Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International) , which allows readers read, download, copy and redistribute the material in any medium or format, provided that the authorship is acknowledged and the material is not used for commercial purposes.