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Title: | Cutting edge localisation in an edge profile milling head |
Authors: | Fernandez-Robles, Laura Azzopardi, George Alegre, Enrique Petkov, Nicolai |
Keywords: | Computer vision Cutting tools Image processing -- Digital techniques Milling cutters |
Issue Date: | 2015 |
Publisher: | Springer, Cham |
Citation: | Fernandez-Robles, L., Azzopardi, G., Alegre, E., & Petkov, N. (2015). Cutting edge localisation in an edge profile milling head.. In G. Azzopardi, & N. Petkov (Eds.), Computer analysis of Images and patterns: 16th International Conference, CAIP 2015, Valletta, Malta, September 2-4, 2015 Proceedings, Part II, LNCS 9257 (pp. 336-347). Springer, Cham. |
Abstract: | Wear evaluation of cutting tools is a key issue for prolonging their lifetime and ensuring high quality of products. In this paper, we present a method for the effective localisation of cutting edges of inserts in digital images of an edge profile milling head. We introduce a new image data set of 144 images of an edge milling head that contains 30 inserts. We use a circular Hough transform to detect the screws that fasten the inserts. In a cropped area around a detected screw, we use Canny’s edge detection algorithm and Standard Hough Transform to localise line segments that characterise insert edges. We use this information and the geometry of the insert to identify which of these line segments is the cutting edge. The output of our algorithm is a set of quadrilateral regions around the identified cutting edges. These regions can then be used as input to other algorithms for the quality assessment of the cutting edges. Our results show that the proposed method is very effective for the localisation of the cutting edges of inserts in an edge profile milling machine. |
Description: | This is a Conference paper presented by the authors at the CAiP 2015: 16th International Conference on Computer Analysis of Images and Patterns, held in Malta from the 2 to 4 September, 2015. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/26586 |
ISBN: | 9783319231174 |
Appears in Collections: | Scholarly Works - FacICTAI |
Files in This Item:
File | Description | Size | Format | |
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Cutting_edge_localisation_in_an_edge_profile_milling_head_2015.pdf | 6.43 MB | Adobe PDF | View/Open |
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