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Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. In this paper an attempt is made to recognize handwritten characters for English alphabets without feature extraction...
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...
Gel electrophoresis (GE) is an important tool in genomic analysis. It is a process of DNA, RNA and protein molecules separation using electric field applied to a gel matrix. This paper describes the image processing techniques applied on GE image to segment the bands from their background. Numerous pre-processing steps are applied on the image prior to the segmentation technique for the purpose of...
Processing Real-Time image sequence is now possible because of advancement of technological developments in digital signal processing, wide-band communication, and high-performance VLSI. With the developments in video technology, the surveillance system can be built with some low cost gadget such as the web-camera. In this modern life with increasing number of crime rate, people in society need for...
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...
This Paper presents a method of mosaicking a series of unidirectional 2-D motional images independent of type of motion in Single Plane i.e. planar or circular in nature, assuming a unidirectional displacement is occurring with each frame. The resultant image after mosaicking can be a color image even though major computation is done on gray scale images and thus making the mosaicking faster and output...
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...
Segmentation of moving objects in an image sequence is one of the most fundamental and crucial steps in visual surveillance applications. This paper proposes a novel and efficient method for detecting moving objects in a noisy background by using a growing self organizing map to construct the codebook. The segmentation process distinguishes between those parts of the objects which move on static and...
Background subtraction is a technique for detecting moving objects in video frames. A simple BS process involves building a model of the background and extracting regions of the foreground (moving objects) with the assumptions that the camera remains stationary and there exist no movements in the background. Video object extraction is a critical task in multimedia analysis and editing. Normally, the...
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...
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...
In this paper, we demonstrate the effectiveness of using statistical shape priors to recover shape descriptors from occluded objects in a level set based variational framework. Parameters that balance curve evolution forces are estimated systematically through embedded discrete Conditional Random Field (CRF). In addition, our approach exploits the benefit of using spectral data to construct a local...
To remove noise from biomedical images polluted by excessive and inhomogeneous additive or multiplicative noise, most of the denoising algorithms cannot keep a desirable balance between denoising and preservation of fine features; only work for one specific noise; and involve heuristic parameter tuning. We present a fully automatic approach to preserve sharp edges and fine details while removing noise...
An adaptive fuzzy c-means (AFCM) clustering based algorithm was developed and applied to the segmentation and classification of multi-color fluorescence in situ hybridization (M-FISH) images, which can be used to detect chromosomal abnormalities for cancer and genetic disease diagnosis. The algorithm improves the classical fuzzy c-means (FCM) clustering algorithm by introducing a gain field, which...
A reliable and accurate method to measure the width of retinal blood vessel in fundus photography is proposed in this paper. Our approach is based on a graph-theoretic algorithm. The two boundaries of the same blood vessel are segmented simultaneously by converting the two-boundary segmentation problem into a two-slice, three-dimension surface segmentation problem, which is further converted into...
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...
Ant Colony Systems (ACS) have been applied to solve complex problems. The first Ant System was proposed in the earlier nineties, and since then several studies were performed to apply this paradigm in real problems. Several researchers have explored the idea of applying ACS to image processing. Herein, the original ACS models applied to image processing are presented. Moreover, two new models, based...
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