Logo Detection Using Pose Clustering and Momentums

Mohammad Hadi Karimi Tafti, Shahram Rajaee, Hossein Sadeghi, Sadegh Tabatabaeifar


Nowadays, logo and arm detection with growing variety and number of arms in companies and countries is one of the significant topics in image processing. For logo detection there are many image processing algorithms which can be used for this purpose regard to features of the logo. In the most of recent works, images are exactly the logos, but in general, the logo can be one portion of another image or even can transform (rotate, skew, shift, …) and have more complexity. In this paper we will select Iran logo as a sample, because it has not any regular geometric form and has special complexity. In a bank of images we will try to find this logo and its position with its transformation. Images bank includes images that has not Iran logo or has Iran logo with affine transform within another pictures. Approaches that will be discussed here are pose clustering and momentum clustering. Simulation results show that this approach can be used as a suitable way for finding the existence and position of arm in this field.


Logo Detection; Pose Clustering; Momentum; Image Processing; Corner Detection

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DOI: http://dx.doi.org/10.18517/ijaseit.1.4.79


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Published by INSIGHT - Indonesian Society for Knowledge and Human Development