JOURNAL ARTICLE

Edge map response of dilated and reconstructed classical filters

Abstract

Edge detection is a basic technique of fundamental feature detection in image processing domain. Dilation of edge filters kernels has proven to bring benefits for the edge detection operation by permitting to filter out noise and to take in consideration a bigger region of the image when processing. Numerous techniques were used in the past for finding edge features, one of the most common used being finding features in lower level scale of the image pyramid. Now, naturally, we want to investigate if our dilating of the filter kernels bring similar benefits as finding edges in a lower scale pyramid level.

Keywords:
Dilation (metric space) Pyramid (geometry) Artificial intelligence Edge detection Computer vision Computer science Filter (signal processing) Enhanced Data Rates for GSM Evolution Image processing Feature (linguistics) Noise (video) Image (mathematics) Feature extraction Pattern recognition (psychology) Mathematics

Metrics

10
Cited By
0.84
FWCI (Field Weighted Citation Impact)
21
Refs
0.74
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering

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