Meet Inspiring Speakers and Experts at our 3000+ Global Conference Series Events with over 1000+ Conferences, 1000+ Symposiums
and 1000+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business.

Explore and learn more about Conference Series : World's leading Event Organizer

Back

Junaid Baber

University of Balochistan
Pakistan

Title: Automatic Image Segmentation for Large Collections

Biography

Biography: Junaid Baber

Abstract

Image segmentation is one of the most significant tasks in computer vision. Since automatic techniques are hard for this purpose, a number of interactive techniques are used for image segmentation. The result of these techniques largely depends on users feedback. It is difficult to get good interactions for large databases. On the other hand, automatic image segmentation is becoming a significant objective in computer vision and image analysis. We propose an automatic approach to detect foreground. We are applying Maximal Similarity Based Region Merging (MSRM) technique for region merging and using image boundary to identify foreground regions. The results confirm the effectiveness of the approach. This approach reveals its effectiveness especially to extract multiple objects from background.