Normalized Cross Correlation

This work represents a comparative study for the methods of registration for dental panoramic X-ray images. The study tried to find the best registration technique used to register images of the jaw. Three image registration techniques are implemented and applied to dental panoramic X-ray images in both spatial domain and wavelet domain. The first technique is based on cross-correlation. The second one depends on selecting control points from both the reference and the input images. The last technique is based on maximization of mutual information between the two images. In the wavelet domain, discrete wavelet transform (DWT) has been performed to the reference image and the test image before the three techniques have been applied. Then the registration methods have been applied using approximation coefficients in the registration procedure. After finishing the registration steps, inverse discrete wavelet transform (IDWT) has been applied in order to obtain the registered image. The...

In the current scenario excessive use of digital media attracted the attention of hackers, attackers and malicious users. In digital media certain types of vulnerabilities are always available, attackers use these vulnerabilities to attack on confidentiality, security, authenticity of digital media. In this paper we have introduced a novel watermarking method based on the properties of Discrete Cosine Transform (DCT) and Permuted Box (P-Box). Using P-Box security of watermark is enhanced up to a great level making it more robust against different image processing attacks. We have used YCbCr color space for watermarking because of its popularity and use in digital photography and video. In the proposed method DCT transform is applied on Cr component of YCbCr and a binary secret image is embedded to middle frequency DCT coefficients of cover image. This proposed method is compared with various previous methods and result shows the effectiveness of the method in terms of robustness, capacity and watermarking attacks.

Standard X-ray images using conventional screen-film technique have a limited field of view and failed to visualize the entire long bone on a single image. To produce images with whole body parts, digitized images from the films that contain portions of the body parts are assembled using image stitching. This article presents a new medical image stitching method that uses minimum average correlation energy filters to identify and merge pairs of X-ray medical images. The effectiveness of the proposed method is demonstrated in the experiments involving two databases that contain a total of 40 pairs of overlapping and nonoverlapping images. Then the experimental results are compared to those of the normalized cross correlation (NCC) method. It is found that the proposed method outperforms the NCC method in identifying both the overlapping and nonoverlapping medical images. The efficacy of the proposed method is further vindicated by its average execution time which is about five times shorter than that of the NCC method. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 166-171, 2012 Copyright © 2012 Wiley Periodicals, Inc.

http://onlinelibrary.wiley.com/doi/10.1002/ima.22018/full

This paper is concerned with the tracking of partially or entirely occluded objects in a video sequence. We propose certain modifications to the template matching approach, which seem to fit the type of tracking data being considered in the present note. Specifically, we will use a nonstandard particle filtering method via the following two steps: The first step employs the normalized cross-correlation function as the likelihood. The second step is to resample, and to fuse the results of multiple cross-correlations of different patches of the given object, in order to refine the likelihood for the particle filter. Experimental results show that the method is reliable for noisy measurements, and provides accurate results in cases of occlusion or heavy shadows.

Diffusion-weighted images are increasingly being employed in conjunction with T2-weighted images for accurate diagnosis of cervical cancer. However, these images suffer from eddy-current related and magnetic field inhomogeneity induced distortions. This paper presents an investigation into the reverse gradient technique to correct distortions in diffusion-weighted echo-planar images of human cervix. We hypothesize that the correction aligns the diffusion-weighted images with the T2-weighted images. To allow for any misalignments and to evaluate the correction, a normalized cross-correlation driven template matching strategy was employed to assess the correlation between the corrected image and the T2-weighted image. For b = 0 smm−2 images, mean correlation values of 0.72±0.14 for regions-of-interest drawn around the cervix for 10 patients were achieved. We also found that our hypothesis was most valid in regions encompassing the cervix with a misalignment of 4.4±3.4mm. Results are presented for images acquired at a field-of-view of 100mm using an endovaginal coil developed in-house for cervix imaging at 3T which is the first of its kind in the world.

In the present work we propose a methodology analysis of the colposcopic images to help the expert to make a more robust diagnosis of precursor lesions of cervical cancer. Although some others approaches have been used to assess cervical lesion, a complete methodology to ...

A fast and accurate iris recognition system is presented for noisy iris images, mainly the noises due to eye occlusion and from specular reflection. The proposed recognition system will adopt a self-customized support vector machine (SVM) and convolution neural network (CNN) classification models, where the models are built according to the iris texture GLCM and automated deep features datasets that are extracted exclusively from each subject individually. The image processing techniques used were optimized, whether the processing of iris region segmentation using iterative randomized Hough transform (IRHT), or the processing of the classification, where few significant features are considered, based on singular value decomposition (SVD) analysis, for testing the moving window matrix class if it is iris or non-iris. The iris segments matching techniques are optimized by extracting, first, the largest parallel-axis rectangle inscribed in the classified occluded-iris binary image, where its corresponding iris region is crosscorrelated with the same subject's iris reference image for obtaining the most correlated iris segments in the two eye images. Finally, calculating the iriscode Hamming distance of the two most correlated segments to identify the subject's unique iris pattern with high accuracy, security, and reliability.

Standard X-ray images using conventional screen-film technique have a limited field of view and failed to visualize the entire long bone on a single image. To produce images with whole body parts, digitized images from the films that contain portions of the body parts are assembled using image stitching. This article presents a new medical image stitching method that uses minimum average correlation energy filters to identify and merge pairs of X-ray medical images. The effectiveness of the proposed method is demonstrated in the experiments involving two databases that contain a total of 40 pairs of overlapping and nonoverlapping images. Then the experimental results are compared to those of the normalized cross correlation (NCC) method. It is found that the proposed method outperforms the NCC method in identifying both the overlapping and nonoverlapping medical images. The efficacy of the proposed method is further vindicated by its average execution time which is about five times shorter than that of the NCC method. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 166-171, 2012 Copyright © 2012 Wiley Periodicals, Inc.

http://onlinelibrary.wiley.com/doi/10.1002/ima.22018/full

This paper is an experimental study to examine the possibility of extracting gastric myoelectric activity (GMA) from photoplethysmographic (PPG) signals. Diagnosing GMA is a clinically challenging task because of its invasive/cumbersome methods. It is known that the PPG consists of information related to heart rate, respiratory rate and phenomena. Here we take this thread further and see whether GMA can