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In this paper, we propose a new lossy image compression algorithm for DICOM ( Digital Imaging and Communications in Medicine) images using Bilinear interpolation. This method presents a technique for classification of the image blocks on the basis of threshold value of variance. The image is divided into [m×n] blocks. Depending on the variance, the block is classified as significant or insignificant...
This paper presents an algorithm to extract the region of interest (ROI) from the palm print image of the Hong Kong PolyU large-scale palm print database (version 2). Competitive coding method is used for feature extraction. Coding based methods are among the most promising palm print recognition methods because of their small feature size, fast matching speed, and high verification accuracy. Competitive...
Face detection is one of the challenging problems in image processing. A novel face detection system is presented in this paper and we propose a new approach using Takagi-Sugeno (T-S) fuzzy model and Hue Saturation and Value (HSV) color model. The algorithm uses fuzzy classifier in conjunction with HSV color model to quickly locate faces in the image. The fuzzy classifier basically examines small...
This paper deals with the recognition of handwritten Malayalam characters. Most of the pattern recognition systems will go through the steps like preprocessing, feature extraction and classification. Here, we have presented edge detection in the preprocessing stage. It is important that the edge detector should give the character edges without fragmentation and displacement of edge pixels. Canny edge...
Handwriting recognition has always been a challenging task in image processing and pattern recognition. India is a multi-lingual, multi-script country, where eighteen official scripts are accepted and there are over a hundred regional languages. The feature extraction method is probably the most effective method in achieving high recognition performance. In this study we proposed a zone-based feature...
Large scale retrieval of handwritten documents has primarily been focused around searching a query text in the OCR'ed transcription of the document images, which provides a limited view of the complete search process. Recent research advances have led to a number of content based retrieval techniques which expand the search scope to document content level (i.e. image features, meta-information). Based...
An approach for the detection of decorative elements - such as initials and headlines - and text regions, focused on ancient manuscripts, is presented. Due to their age, ancient manuscripts suffer from degradation and staining as well as ink is faded-out over the time. Identifying decorative elements and text regions allows indexing a manuscript and serves as input for Optical Character Recognition...
In this paper, a two-stage scheme for the recognition of Persian handwritten isolated characters is proposed. In the first stage, similar shaped characters are categorized into groups and as a result, 8 groups are obtained from 32 Persian basic characters. In the second stage, the groups containing more than one similar shape characters are considered further for the final recognition. Feature extraction...
This paper, presents a new cephalometric landmark localization method based on combining two classifier results. Initially, a classifier based on histograms of oriented gradients makes a first estimation of the potential windows, and then a second classifier, based on histograms of gray profile, classifies the detected windows. By combining the results of these two classifiers, final decision is made...
In this paper, we propose a method to recognize periodic gestures from images. The proposed method uses a amplitude spectrum and a phase spectrum that are obtained by applying Fast Fourier Transform (FFT) to a time series of intensity images. FFT is applied to each pixel of low-resolution images. The method consists of 2 steps. First, the method detects periodic motion regions from the amplitude spectrum...
In the majority of cases blindness is caused by retinal degenerative conditions such as Age-Related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP). However, blind individuals still retain central visual pathways and processing mechanisms. Recent advances in Time of Flight (TOF) imaging technology have presented new opportunities to develop improved sensory substitution systems for compensation...
A satellite precipitation estimation algorithm based on wavelet features is investigated to find the optimal wavelet features in terms of wavelet family and sliding window size. In this work, the infrared satellite based images along with ground gauge (radar corrected) observations are used for the retrieval rainfall. The goal of this work is to find an optimal wavelet transform to represent better...
Breast cancer is the most common cancer in many countries all over the world. Early detection of cancer, in either diagnosis or screening programs, decreases the mortality rates. Computer Aided Detection (CAD) is software that aids radiologists in detecting abnormalities in medical images. In this article we present our approach in detecting abnormalities in mammograms using digital mammography. Each...
An attempt has been made in the paper to find globally optimal cluster centers for remote-sensed images with the proposed Rapid Genetic k-Means algorithm. The idea is to avoid the expensive crossover or fitness to produce valid clusters in pure GA and to improve the convergence time. The drawback of using pure GA in the problem is the usage of an expensive crossover or fitness to produce valid clusters...
Text recognition in ancient documents poses specific challenges such as degradation and staining, fading out of ink, fluctuating text lines, superimposing of text-elements or varying layouts, amongst others. To cope with those challenges, a texture-based approach is proposed, which exploits the fact that different kinds of textures have distinct orientation distributions. The orientation information...
Recent studies have shown that convolutional networks can achieve a great deal of success in high-level vision problems such as objection recognition. In this paper, convolutional networks are used to solve a typical low-level image processing task, image segmentation. Here, the convolutional networks are trained using gradient descent techniques to solve the problem of segmenting the cell nuclei...
In this paper, we propose a novel approach to stable near and long range perception for various complex outdoor environments. Our techniques cope robustly with near-range road estimation using a laser scanner and long-range terrain classification using a color camera. Near-range road surface conditions are estimated by using information of remission value as reflectivity of a laser. We apply graph...
Traffic Signs provide drivers with very valuable information about the road, in order to make driving safer and easier. They are designed to be easily recognized by human drivers mainly because their color and shape are very different from natural environments. Automatic traffic sign detection and recognition is important in the development of unmanned vehicles, and is expected to provide information...
The study of traffic sign recognition system has been of great interests for many years. This problem is often addressed by a three-stage procedure involving detection, tracking and classification. In this paper, a novel approach combining detection and classification of circular traffic signs is proposed. The position and scale of sign candidates within the scene are captured by detecting the center...
This paper proposes an Adaptive Fuzzy Classifier Approach (AFCA) to local edge detection in order to address the challenges of detecting latent fingerprint in severely degraded images. The proposed approach adapts classifier parameters to different parts of input images using the concept of reference neighborhood. Three variants of AFCAs, namely K-means-clustering AFCA, Entropy-based AFCA, and Statistical...
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