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 Comp- onent 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 pat- ches 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 re- sults.
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 11.
Available at: https://www.interscience.in/ijssan/vol1/iss2/11