Object Detection Using Diversified Search by Measuring Objectness of Image Window
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
Object Detection and recognition is an important job in remote sensing and automation. Conventional object detection approaches are usually not sufficiently sturdy in addressing the variations of targets and typically suffer from restricted training samples. Search of possible object position in the image is also a restricting situation in object detection and needs to find a solution. This paper introduces a robust object detection approach which combines the diversified search approach and segmentation strategies. In proposed work, we tend to aim to capture all potential object locations. Rather than one technique to come up with potential object locations, we tend to diversify our search and use a range of complementary image partitioning to include all the possible conditions. As number of locations are reduced for search, this results in speeding up the searching process. Experimental results prove that the proposed method is efficient in reaching convergence quickly and gives better quantitative result.
Authors and Affiliations
Preeti Sinha, Toran Verma
Keywords
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- EP ID EP20978
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