Efficient color edge detection based on synthetic weighted multi-structure element morphology

Phairoj Samutrak; Jeeraporn Werapun

doi:10.1117/12.2051035

10 January 2014 Efficient color edge detection based on synthetic weighted multi-structure element morphology

Phairoj Samutrak, Jeeraporn Werapun

Proceedings Volume 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013); 90691C (2014) https://doi.org/10.1117/12.2051035
Event: Fifth International Conference on Graphic and Image Processing, 2013, Hong Kong, China

Abstract

Applying the structure element (SE)-based morphology to detect the edges of the image corrupted by noise may obtain the irregular shape, and hence the precision of the object identification may decrease. Lately, the multi-SE morphology was introduced to detect the edge of gray-scale image, which yields the more integral and continual final result than that of the single-structure element. For color images, the robust color morphology gradient (RCMG) edge-detection, extended from CMG, was proposed by using a square SE along with the removing outliner technique to solve the noisesensitivity problem. In this paper, in order to solve such a noise problem on color images, we propose an efficient color edge-detection algorithm, called the ECMSEM (Efficient Color Multi-SE Morphology) by combining the advantage of the multi-SE morphology and the removing (noise) outliner. In our ECMSEM approach, the color multi-SE morphology with using a synthetic weighted method is introduced to detect only edge (except noise) and using multi-scale SEs to increase the precision of each SE-direction, and hence improve the edge-detection results. In performance evaluation, the edge-detection results (of synthetic color tested images) showed that our ECMSEM yielded the higher FOM than those of the RCMG approach.

Citation Download Citation

Phairoj Samutrak and Jeeraporn Werapun "Efficient color edge detection based on synthetic weighted multi-structure element morphology", Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90691C (10 January 2014); https://doi.org/10.1117/12.2051035

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KEYWORDS

Edge detection

Sensors

Detection and tracking algorithms

RGB color model

Image processing

Selenium

Image segmentation

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