This paper presents a template-based approach to detect objects of interest from real images. We rely on AM-FM models and specifically, on the Dominant Component Analysis (DCA) for feature extraction. We incorporate the results from AM-FM models for object detection. In order to detect the object of interest from real images patches are introduced. In order to find the degree of match between the patch and template, the AM-FM features are calculated. To find the correlation between the template and image patch, mean and standard deviation of image patch and template are calculated. If this correlation value exceeds a preset detection threshold, we declare that patch contains the object of interest. The combination of AM-FM features and template based object detection produces efficacious results.
Nagaraju, K. Shanmukha; Reddy, B. Eswara Dr.; and Reddy, P. Chandra Sekhar
"OBJECT DETECTION USING AM-FM FEATURES,"
International Journal of Smart Sensor and Adhoc Network: Vol. 1
, Article 2.
Available at: https://www.interscience.in/ijssan/vol1/iss2/2