APPAREL PRODUCTION MONITORING SYSTEM USING IMAGE RECOGNITION

• US 20190311470A1
• Filed: 03/08/2019
• Published: 10/10/2019
• Est. Priority Date: 04/10/2018
• Status: Abandoned Application

• Current Assignee: ONS communication Co.
• Original Assignee: ONS communication Co.
• Inventors: Lee, Kang-Kwon, Chu, Kyung-Wan, Kang, Yoo-Seok, Cho, Sang-Wook
• Application Number:
  US16/296,763
• Publication Number:
  US 20190311470A1
• Time in Patent Office: Days
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/30124 Fabrics; Textile; Paper
• CPC Class Codes: G06T 2207/30242 Counting objects in image
• CPC Class Codes: G06T 7/001 using an image reference approach
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/62 of area, perimeter, diameter or volume
• CPC Class Codes: G06V 10/44 Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 2201/06 Recognition of objects for industrial automation
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources

Abstract

Provided is an apparel production monitoring system using image recognition, including: a first camera module that takes an image of apparel products; and a monitoring device that analyzes the image of the apparel products to grasp the number and sizes of the apparel products, receives a transmission image of the apparel products, and compares and analyzes it with a previously learned transmission image to detect a defect of the apparel products.

Claims

1. A apparel production monitoring system using image recognition, comprising:

a first camera module that takes an image of apparel products; and

a monitoring device that analyzes the image of the apparel products to grasp the number and sizes of the apparel products, receives a transmission image of the apparel products, and compares and analyzes it with a previously learned transmission image to detect a defect of the apparel products.

2. The apparel production monitoring system of claim 1,

wherein the monitoring device computes pixel characteristics of a background image acquired before the first camera module takes the image of the apparel products, sets a first region of interest in the background image, sets a second region of interest in the image of the apparel products, computes a difference in pixel characteristics between an image of an apparel product in the second region of interest and a background image in the first region of interest, perform binarization to a result of the computed difference and thus recognize an object of the apparel product from the binarized image.

3. The apparel production monitoring system of claim 2,

wherein the monitoring device updates pixel characteristics of the background image based on pixel characteristics of a background included in the image of the apparel products.

4. The apparel production monitoring system of claim 1, further comprising:

a second camera module configured to take an image of the side of multiple overlapping apparel products,

wherein the monitoring device acquires a first thickness of an apparel product from a previously learned image of the apparel products, acquires a second thickness of the multiple overlapping apparel products from the image of the side of the multiple overlapping apparel products, and grasps the number of the multiple overlapping apparel products from the first thickness and the second thickness.

5. The apparel production monitoring system of claim 1,

wherein the monitoring device acquires a pattern of the apparel product from the image of the apparel products and compares and analyzes it with a previously learned pattern in an apparel material image to grasp a material of the apparel product.

6. The apparel production monitoring system of claim 1,

wherein the monitoring device extracts a contour image of the apparel product from the image of the apparel products and compares and analyzes it with a previously learned contour image for each kind of apparel product to grasp the kind of the apparel product.

7. The apparel production monitoring system of claim 1,

wherein the monitoring device detects edges from the image of the apparel product and sets the edges as feature points, acquires shapes of the feature points, and calculates a maximum vertical length and a maximum horizontal length of the apparel product from the feature points to grasp the size of the apparel product from the maximum vertical length and the maximum horizontal length.

8. The apparel production monitoring system using image recognition of claim 1,

wherein the defect of the apparel products includes a logo error, a thread, color bleeding, a needle, and a defective design pattern.

9. The apparel production monitoring system of claim 8,

wherein the monitoring device previously learns a transmission image for each defect of the apparel products and stores a learning result file for each defect of the apparel products and loads the learning result file at the time of defect inspection of the apparel products, and compares and analyzes it with the transmission image of the apparel products to grasp the kind of defect of the apparel products and the location of the defect in the apparel products.

10. An apparel production monitoring device using image recognition, comprising:

an image acquisition unit that receives an image of apparel products taken by a camera module and receives a transmission image of the apparel products;

a product count unit that counts the number of the apparel products based on the image of the apparel products;

a product sensing unit that senses information of the apparel products based on the image of the apparel products; and

a defect detection unit that detects a defect of the apparel products by comparing and analyzing the transmission image of the apparel products with a previously learned transmission image.