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This work introduces techniques to facilitate large-scale Augmented Reality (AR) experiences in unprepared outdoor environments. We develop a shape-based object detection framework that works with limited texture and can robustly handle extreme illumination and occlusion issues. The contribution of this work is a purely geometric approach for detecting marker-like objects under difficult and realistic...
Background subtraction is a process of separating moving foreground objects from the non-moving background. This technique must adapt to the illumination, motion and the geometry background changes such as shadow, reflections, and etc. In this paper, one of the traditional background subtraction techniques which is frame differencing (FD) is conducted to detect the moving object in outdoor environment...
Human heart anatomy is the study of morphological structures and relationships between morphological structures. Hence such a study when visualized in the form of a two dimensional atlas can hold strong interactive sessions between doctors and medical students. Atlas is a visualization technique developed for understanding the morphological structures of a human body. Interacting directly with morphological...
Texture features alone cannot help us to recognize faces, because there may be several people with similar texture features. Likewise geometry based features can also be similar in different people. When the two methods are experimented separately, there may be inaccurate results. There might be better results when the two methods are combined and used. So this paper tries to evaluate the performance...
Character segmentation has long been a critical area of the Optical Character Recognition. In this paper, we present an algorithm for character segmentation for Indic and Roman scripts. Character segmentation is difficult for Indic scripts because in these scripts characters are connected with the Shirorekha or headline and the regions bounding the two consecutive characters might overlap because...
We develop a new perspective invariant feature space representation of remotely sensed objects, regarding the features themselves as primitive observables of the 3D objects and to estimate them from multiple sensor measurements. This is formulated as an inverse problem in the feature coefficients. Once the coefficients are estimated they may be used to derive higher level features used by machine...
This project presents MySQL database for storage of fingerprint data. The application of the database is for future process, fingerprint matching. In this project, Matlab R2009 is the software used for fingerprint image enhancement and minutia extraction. MySQL is a relational database management system (RDBMS) that runs as a server providing multi-user access to a number of databases. XAMPP Control...
We present a method for improving human segmentation results in calibrated, multi-view environments using features derived from both pixel (image) and voxel (volume) space. The main focus of this work is to develop a low-cost, vision-based system for passive activity monitoring of older adults in the home, to capture early signs of illness and functional decline and allow seniors to live independently...
With the development of the Broadcasting and Video network, the Monitoring System on Digital Video Broadcasting is becoming more and more important. Image recognition technology is widely applied to detect the degraded video in the television observation system. Mosaic block easily occurs in the TV signals, which will degrade the video quality. The conventional mosaic detection algorithm can't distinguish...
Face recognition is a challenging problem in computer vision and human computer interaction. Texture is the surface property which is used to identify and recognize objects in an image. Texture based facial recognition is a fast growing research area in recent years. The LBP method is based on characterizing the local image texture by local texture patterns. In this paper texture based face recognition...
Everyday medical is capturing thousands of images which need to be classified in a proper way. In this paper, we address the problem of replacing the existing images with the captured one. We provide a new solution by storing only the nonexisting part of the image. Though medical images have been classified in past by using various techniques, the researchers are always finding alternative strategies...
The Human Protein Atlas (HPA) is a repository of location patterns of about 11000 proteins within tissues and cell lines. In this work we summarize some of our current work on analyzing immunohistochemical images of proteins within 7 distinct tissues. Firstly, we present our efforts to analyze spatial point patterns of protein staining and determine protein subcellular location from image-derived...
In this paper, a new method that incorporates the spatial information to localize prostate cancer with magnetic resonance imaging (MRI) is proposed. Most automated methods for tumor localization require manual peripheral zone extraction from the prostate gland, and it is a tedious and time-consuming job with considerable inter-observer variability. In order to conquer this difficulty, we propose to...
Facial rejuvenation has driven a lot of research in the field of dermatology and plastic surgery, leading to many medical procedures. This paper proposes an age prediction method that could be used to better understand the ageing process and to evaluate the benefits of a rejuvenating treatment, for example. A supervised Facial Model (SFM) is built using Partial Least Squares regression (PLSR) to capture...
A novel interactive segmentation method based on distance metric learning is proposed for segmentation of tumors in CT and MRI images. Firstly, the moments of the gray-level histogram are extracted as the image features for segmentation. Then, Neighborhood Components Analysis is employed to learn a task-specific distance metric in the feature space using the interactive inputs. The probability of...
Centerline extraction is widely used in medical image processing. It can benefit applications such as building the connectivity map of neurons from microscopic images as well as examining retina vessels for preventing blindness. Many methods have been developed to extract centerlines from 2-D images. An algorithm based on 2-D rapid tensor voting is proposed in this paper. This method uses the Canny...
Among the most critical components of a computerized system for automated melanoma detection is image sampling and pooling of the extracted features. In this paper, we propose a new method for sampling and pooling based on a combination of spatial pooling and graph theory features. The performance of the new method is evaluated using a dataset of more than 1,500 images representing pigmented skin...
This paper presents an algorithm to classify pixels in uterine cervix images into two classes, namely normal and abnormal tissues, and simultaneously select relevant features, using group sparsity. Because of the large variations in image appearance due to changes of illumination, specular reflections and other visual noise, the two classes have a strong overlap in feature space, whether features...
This work proposes a new methodology for the extraction of Harmonic Phase images in cardiac tagged Magnetic Resonance Imaging. The procedure draws upon the use of the Windowed Fourier Transform, which provides a spatially varying representation of the signal spectra. The spectral peaks of the local Fourier domain are then extracted by a conventional Harmonic Phase recovering technique in such a way...
Knife Edge Scanning Microscopy (KESM) is a high-throughput imaging technique used to obtain large-scale anatomical information (≈1cm3) at sub-micrometer resolution. Data acquisition has been fully automated, however significant post-processing and reconstruction must be done manually. KESM is unique in that illumination and tissue sectioning are performed using a diamond knife. Therefore many of the...
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