This paper presents an efficient approach to rotation discriminative template matching. A hierarchical search divided in three steps is proposed. First, gradient magnitude is compared to rapidly localise points with high probability of match. This result is refined, in a second step, using orientation gradient histograms. A novel rotation discriminative descriptor is applied to estimate the ori...

We address the problem of finding point correspondences in images by way of an approach to template matching that is robust under affine distortions. This is achieved by applying “geometric blur” to both the template and the image, resulting in a fall-off in similarity that is close to linear in the norm of the distortion between the template and the image. Results in wide baseline stereo corre...

A coarse-to-fine approach to object location via template matching is described that entails the progression from sparse to full templates, and the progression from large step to small step "marching" of the templates through an image. Our "coarse-tofine" approach may be loosely described as "multi-grid" or "multi-resolution" although it differs in significant detail from previous work. The app...

We propose a novel technique that significantly improves the performance of oriented chamfer matching on images with cluttered background. Different to other matching methods, which only measures how well a template fits to an edge map, we evaluate the score of the template in comparison to auxiliary contours, which we call normalizers. We utilize AdaBoost to learn a Normalized Oriented Chamfer...

The paper aims at developing a hierarchical algorithm for matching a given template of × on an image of × pixels partitioned into equal sized blocks of × pixels. The algorithm employs a fuzzy metric to measure the dispersion of individual feature of a block with respect to that of the template. A fuzzy threshold, preset by the user, is employed to restrict less likely blocks from participation ...

A new two-stage approach for robust estimation of large image motion is proposed. We first use template matching to find large image motion up to pixel-level accuracy and then use the differential technique to refine the image motion to subpixel accuracy. Experimental results have shown that the proposed approach can estimate visual motion both robustly and accurately. Indexing terms: Motion es...

We study a class of mathematical and statistical algorithms with the aim of establishing a computer-based framework for fast and reliable automatic abnormality detection on landmark represented image templates. Under this framework, we apply a landmark-based algorithm for finding a group average as an estimator that is said to best represent the common features of the group in study. This algor...

As an ongoing effort to develop a computer aided system for the detection of masses on mammograms, we propose on this work a new model-based segmentation algorithm. The algorithm is based on a template matching scheme by using the mutual information approach in the similarity metric. Thus, the system will be able to determine if it exists a true mass on the studying image. The proposal was deve...

Template matching is a well-proven approach in the area of articulated object tracking. Matching accuracy and computation time of template matching are essential and yet often conflicting goals. In this paper, we present a novel, adaptive template matching approach based on the silhouette area of the articulated object. With our approach, the ratio between accuracy and speed simply is a modifia...

This paper presents an approach for recognizing urban scene in distant views. Previously, we have developed a method using dynamic programming technique to recognize key buildings appearing as silhouette in a distant view. Based on those locations of buildings in silhouette, this paper develops a method to find locations of other buildings which do not appear as silhouette in the image by using...