Template matching by normalized cross correlation (NCC) is widely used for finding image correspondences. We improve the robustness of this algorithm by preprocessing images with "siamese" convolutional networks trained to maximize the contrast between NCC values of true and false matches. The improvement is quantified using patches of brain images from serial section electron microscopy. Relat...

In recent years, the accelerated growth in the field of computer vision, image fusion, medical imaging, military automatic target recognition, remote cartography and astrophotography has established the need for the development of good image registration technique for the efficient retrieval of interest point area. Image registration is the process of geometrically aligning one image to another...

Normalized cross correlation (NCC) has been used extensively in machine vision for industrial inspection, but the traditional normalized correlation suffers from false alarms for the image that contains both complicated and uniform patterns in individual small regions. In this paper, we study the use of NCCs for defect detection in complicated images. The effect of NCCs in gray-level and color ...

In this paper, we present an algorithm for extracting translations of any given multiword expression from parallel corpora. Given a multiword expression to be translated, the method involves extracting a short list of target candidate words from parallel corpora based on scores of normalized frequency, generating possible translations and filtering out common subsequences, and selecting the top...

Digital image-based elasto-tomography (DIET) is an emerging method for non-invasive breast cancer screening. Effective clinical application of the DIET system requires highly accurate motion tracking of the surface of an actuated breast with minimal computation. Normalized cross correlation (NCC) is the most robust correlation measure for determining similarity between points in two or more ima...

Local image matching (block-matching) is a frequent operation in many image processing tasks, such as MPEG compression and the estimation of optical flow and stereo disparities. Normalized cross-correlation (NCC) is particularly useful since it is insensitive to both signal strength and level. However, NCC is computationally expensive. In this article we attempt to speed up NCC first by transfo...

A novel feedback-based spike detection algorithm for noisy spike trains is presented in this paper. It uses the information extracted from the results of spike classification for the enhancement of spike detection. The algorithm performs template matching for spike detection by a normalized correlator. The detected spikes are then sorted by the OSortalgorithm. The mean of spikes of each cluster...

Image correspondence and registration techniques have gained popularity in recent times due to advancement of utilization in digital media and its storage. The main problem associated with image processing is when it is applied to fields like robotic vision and machine vision. The problem is due to clutter, i.e. the same frame with different objects has to be matched. Hence there has been need ...

One of the difficulties in obtaining a dense and accurate disparity map through stereo matching is the presence of radiometric variation in the two images used in this process.It is commonly assumed that in stereo matching, the corresponding pixels have similar pixel values. But the presence of this variation causes the regular methods to produce erroneous results. In this paper, we use the con...

This paper analyzes the performance of sum of squared differences (SSD), sum of absolute differences (SAD), normalized cross correlation (NCC), zero mean normalized cross correlation (ZNCC) and several other proposed modified expressions of NCC. Experimental results on real images demonstrate that some of the proposed modified expressions of NCC are more efficient than conventional NCC for temp...