Electronic Letters on Computer Vision and Image Analysis (ELCVIA - Universitat Autònoma de Barcelona)
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From medical data to simple virtual mock-up of scapulo-humeral joint
Get PDFThe surgical operations of shoulder joint are guided by various principles: osteosynthesis in the case offracture, osteotomy in order to correct a deformation or to modify the functioning of the joint, or implementationof articular prosthesis. At the end of the twentieth century, many innovations in the domains of biomechanicsand orthopedic surgery have been performed. Nevertheless, theoretical and practical problems may appearduring the operation (visual field of surgeon is very limited, quality and shape of the bone is variable dependingon the patient). Biomechanical criteria of success are defined for each intervention. For example, the installationwith success of prosthetic implant will be estimated according to the degree of mobility of the new articulation,the movements of this articulation being function of the shape of the prosthesis and of its position on its osseoussupport. It is not always easy to optimize the preparation of the surgical operation for every patient, and apreliminary computer simulation would allow helping the surgeon in its choices and its preparation of theintervention. The techniques of virtual reality allow a high degree of immersion and allow envisaging thedevelopment of a navigation device during the operating act
Non-Model Based Method for an Automation of 3D Acquisition and Post-Processing
Get PDFMost of the automation for 3D acquisition concerns objects with simple shape, like mechanical parts. Forcultural heritage artefacts, the process is more complex, and it doesn\u27t exist general solution nowadays. Thispaper presents a method to generate a complete 3D model of cultural heritage artefacts. In a first step, MVC isused to solve the view planning problem. Then, holes remaining in 3D model are detected, and their features arecalculated to finish acquisition. Different post-processing are applied on each view to increase quality of the 3Dmodel. This procedure has been tested with simulated scanner, before being implemented on a motion systemwith five degrees of freedom
Realtime Kernel based Machine Learning Template Matching (KMLT)
No full textThis paper deals with a new approach for the problemof realtime planar templatematching. We considertracking as the estimation of a parametric function between observations and motion and we propose anextension of the learning based approach presented simultaneously by Cootes and al. and by Jurie andDhome to non linear regression functions. The estimation of the linear parameters associated to the basisfunctions (kernel functions) of the model is then achieved using a training set of motions and associatedobservations. We show that the resulting method outperforms the robustness of the linear tracker againstnoisy observations
A SVD Based Scheme For Post Processing of DCT Coded Images
Get PDFIn block discrete cosine transform (DCT) based image compression, the blocking artifacts are the main cause of degradation, especially at higher compression ratio. In proposed scheme, monotone or edge blocks are identified by examining the DCT coefficients of the block itself. In the first algorithm of the proposed scheme, a signal adaptive filter is applied to sub-image constructed by the DC components of DCT coded image to exploit the residual inter-block correlation between adjacent blocks. To further reduce artificial discontinuities due to blocking artifacts, the blocky image is re-divided into blocks in such a way that the corner of the original blocks comes at the center of the new blocks. These discontinuities causes the high frequency components in the new blocks. In this paper, these high frequency components due to blocking artifacts in monotone area are eliminated using singular value decomposition (SVD) based filtering algorithm. It is well known that the random noise is hard to compress, whereas it is easy to compress the ordered information. Thus, lossy compression of noisy signal provides the required filtering of the signal itself
Restoration of Videos Degraded by Local Isoplanatism Effects in the Near-Infrared Domain
Get PDFWhen observing a scene horizontally at a long distance in the near-infrared domain, degradations dueto atmospheric turbulence often occur. In our previous work, we presented two hybrid methods to restorevideos degraded by such local perturbations. These restoration algorithms take advantages of a space-timeWiener filter and a space-time regularization by the Laplacian operator. Wiener and Laplacian regularizationresults are mixed differently depending on the distance between the current pixel and the nearest edge point.It was shown that a gradation betweenWiener and Laplacian areas improves results quality, so that only thealgorithm using a gradation will be used in this article.In spite of a significant improvement in the obtained images quality, our restoration results greatly dependon the segmentation image used in the video processing. We then propose a method to select automaticallythe best segmentation image
Gait Identification Considering Body Tilt by Walking Direction Changes
Get PDFGait identification has recently gained attention as a method of identifying individuals at a distance.
Thought most of the previous works mainly treated straight-walk sequences for simplicity, curved-walk sequences
should be also treated considering situations where a person walks along a curved path or enters a
building from a sidewalk. In such cases, person’s body sometimes tilts by centrifugal force when walking
directions change, and this body tilt considerably degrades gait silhouette and identification performance,
especially for widely-used appearance-based approaches. Therefore, we propose a method of body-tilted silhouette
correction based on centrifugal force estimation from walking trajectories. Then, gait identification
process including gait feature extraction in the frequency domain and learning of a View Transformation
Model (VTM) follows the silhouette correction. Experiments of gait identification for circular-walk sequences
demonstrate the effectiveness of the proposed method
Robust Focusing using Orientation Code Matching
Get PDFThis paper proposes a novel scheme for image focusing by introducing a new focus measure based on self-matching methods. A unique pencil-shaped profile is identified by comparing the similarity between all patterns extracted around the same position in each scene. Based on this profile, a new criterion function called Complementary Pencil Volume (hereafter CPV) is defined to evaluate focused or defocused scenes based on similarity rate of self-matching, which visually represents the volume of a pencil-shaped profile. Among matching methods, Orientation Code Matching (hereafter OCM) is recommended due to its invariance with regards to illumination and contrasts. Several experiments using a telecentric lens are implemented to demonstrate the efficiency of proposed measures. Outstandingly, comparing Orientation Code Matching-based (hereafter OCM-based) focus measure with conventional focus measures shows that OCM-based focus measure is robust against changes of illuminations and contrast. Using this method, depth is measured by comparing the focused and defocused region in the scenes both under high and low illumination conditions
Detection of Masses in Digital Mammograms using K-Means and Support Vector Machine
Get PDFFemale breast cancer is a major cause of death in occidental countries. CAD/CADx systems can aidradiologists in detection and diagnostic of lesions in mammograms. In this work, we present a methodologyto detect masses from mammograms. The K-means clustering algorithm is used to split the mammogramsin regions. Each region is then classified through a Support Vector Machine (SVM) as mass or non-massregion. SVM is a machine-learning method, based on the principle of structural risk minimization, whichperforms well when applied to data outside the training set. We use a set of textural and shape measures todetect suspicious regions, as bening and malignant masses. Each textural measure (contrast, homogeneity,inverse difference moment, entropy and energy) is computed through the co-ocurrence matrix technique.The methodology obtained an accuracy of 93.11% discriminate mass from non-mass elements
A New Image Fusion Technique Based on Directive Contrast
Get PDFFor making an image, which is more suitable for segmentation, feature extraction, object recognition, and Human Visual System, image fusion is frequently used technique. It combines complimentary information from different images of the same scene in a single image. In this paper, a simple but efficient algorithm is presented for image fusion employed in wavelet packet domain. For fusion, all the source images are decomposed into low and high frequency sub-bands and then fusion of high frequency sub-bands is done by the means of Directive Contrast while for low frequency median values is used. To reconstruct the fused image, inverse wavelet packet transform is performed. The performance of the algorithm is carried out by the experimental evaluation and the comparison is carried out with the existing algorithm