template matching of colored image based on quaternion fourier transform and image pyramid techniques

Template matching method is one of the most significant object recognition techniques and it has many applications in the field of digital signal processing and image processing and it is the base for object tracking in computer vision field. The traditional template matching by correlation is performed between gray template image w and the candidate gray image f where the template’s position is to be determined in the candidate image. This task can be achieved by measuring the similarity between the template image and the candidate image to identify and localize the existence of object instances within an image. When applying this method to colored image, the image must be converted to a gray one or decomposed to its RGB components to be processed separately. The current paper aims to apply the template matching technique to colored images via generating the quaternion Fourier transforms of both the template and candidate colored image and hence performing the cross-correlation between those transforms. Moreover, this approach is improved by representing both the image and template as pyramid multi-resolution format to reduce the time of processing. The proposed algorithm is implemented and applied to different images and templates using Matlab functions.