Problem statement: Template matching is a famous methodology that has a wide range of applications in image and signal processing. For a template and input image, template matching methodology finds the partial input image that is most closely matches the template image in terms of specific criterion such as the Euclidean distance or cross-correlation. Approach: In this study, a fast and robust...

Most research related to automated analysis of music presupposes human partitioning of the input into segments corresponding to significant harmonic or melodic chunks. In this paper, we describe HarmAn, a system that partitions tonal music into harmonically significant segments corresponding to single chords and labels these segments with the proper chord labels. Segment labels are determined t...

A technique for classifying variable objects using flexible template models is described. A model representing each class of object is generated from training examples and during recognition each model is fitted to the input image. The object represented by the model that maximises a fit measure is recognised as the input. The method has been tested on plant seeds, handprinted characters and hu...

The main aim of this study is to propose efficient algorithms for image template matching on parallel machines. To our knowledge there is no a template matching algorithm that converts the template image and all candidate blocks in the source image from two-dimensions into one-dimension. This study proposes a Template Matching Vectoring Algorithm (TMVA) that reduces the amount of data to be ana...

This paper represents a template matching using statistical model and parametric template for multi-template. This algorithm consists of two phases: training and matching phases. In the training phase, the statistical model created by principal component analysis method (PCA) can be used to synthesize multi-template. The advantage of PCA is to reduce the variances of multi-template. In the matc...

Although it is well known that cross correlation can be efficiently implemented in the transform domain, the normalized form of cross correlation preferred for template matching applications does not have a simple frequency domain expression. Normalized cross correlation is usually computed in the spatial domain for this reason. This short paper shows that unnormalized cross correlation can be ...

Textual image compression is a method of both lossy and lossless image compression that is particularly effective for images containing repeated sub-images, notably pages of text (Mohiuddin et al., 1984; Witten et al., 1992). The process comprises three main steps: Extracting all the characters from an image; Building a library that contains one representative for each character class; Compress...

We consider the problem of locating a template as a subimage of a larger image. Computing the maxima of the correlation function solves this problem classically. Since the correlation can be calculated with the Fourier transform this problem is a good candidate for a superior quantum algorithmic solution. We outline how such an algorithm would work.

By exploiting an analogy with averaging procedures in fluid dynamics, we present a set of averaged template matching equations. These equations are analogs of the exact template matching equations that retain all the geometric properties associated with the diffeomorphism group, and which are expected to average out small scale features and so should, as in hydrodynamics, be more computationall...