Sunday 21st of January 2018

Automatic Quick-Shift Segmentation for Color Images

Abdelhameed Ibrahim

This paper proposes an automatic quick-shift segmentation method using illumination invariant representation of natural color images. In practice, the quick-shift segmentation method is sensitive to the choice of parameters, thus a quick tuning by hand is not sufficient. The proposed method segments images into homogeneous regions by applying the quick-shift method with initial values, then changes the quick-shift parameters values automatically to get the final segmented image. Changing parameters values make the proposed method flexible and robust against different image characteristics. We eliminate the factors that may affect natural image acquisition such as shadow and highlight by applying an invariant method. This method is valid for large size images. The effectiveness of the proposed method for a variety of images including different objects of metals and dielectrics is examined in experiments.

Keywords: Quick-shift; color image segmentation; invariant representation

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Abdelhameed Ibrahim
Abdelhameed Ibrahim was born in Mansoura city, Egypt, in 1979. He attended the Faculty of Engineering, Mansoura University, in Mansoura, where he received Bachelor and Master Degrees in Engineering from the electronics (Computers Engineering and Systems) department in 2001 and 2005, respectively. He was with the Faculty of Engineering, Mansoura University, from 2001 through 2007. In April 2007, he joined the Graduate School of Advanced Integration Science, Faculty of Engineering, Chiba University, Japan, as a doctor student. He received Ph.D. Degree in Engineering in 2011. His research interests are in the fields of computer vision and pattern recognition, with special interest in material classification based on reflectance information.

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