Text Region Extraction in a Document Image Based on Discrete Wavelet transforms

Audithan, S.; Chandrasekaran, R. M.

doi:10.20894/ijmsr.117.002.001.005

Cited by 14 publications

(15 citation statements)

References 2 publications

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“…The case study of a 2-D Haar wavelet transformation is investigated to initiate secure processing of data. Audithan and Chandrasekaran [12], study the implementation of an effective and high computational speed persisting method that could extract the regions of text from a present document. The study stresses over introducing Haar DWT that has the fastest operational speed when compared to all the other wavelets as it has coefficients either set as -1 or 1.…”

Section: Review Of Literaturementioning

confidence: 99%

An Optimized FPGA Based System Design for the Arrhythmia Detection using ECG

C*,

S V

2019

IJITEE

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Electrocardiogram signals are highly susceptible to interferences caused due to various kinds of noises including artefacts’, disruptions in power lines attained from the human interferences and device disturbances. These noise signals tend to lower the quality of signals that result in crucial environment for detecting and diagnosing different types of arrhythmia. In order to avoid this issue, multiple filtering techniques are being incorporated out of all Gaussian filters with Haar DWT portray better outcomes in noise elimination and smoothening of signal. The process of ECG signal filtering allows performing the testing and validation of in the actual world emulation. Enhancement in PSNR ratio is observed by using the ECG signal filters along the reconstructed signal. For a given input ECG signal, the levels of the signal peak decide if the patient is suffering from arrhythmia or not. If peak is low, patient is detected with the arrhythmia disease, if high patient is normal. The results can be observed in simulation. FPGA prototyping of the design is carried out along the hardware debugging in chip scope pro tool. The design is realized using Verilog coding with the technique of morphological filtering. For the purpose of debugging the hardware device used is Artix-7. The FPGA methodology is success full in a position to detect arrhythmia. The framework based on FPGA is structured and executed in the paper which can detect a type of arrhythmia which indicates Atrio Ventricular block along with all the noises removed. The simulation results are obtained by taking ECG signals from MIT-BIH arrhythmia database. The proposed FPGA based system design is proven to be optimized as it showed very less utilization of resources when compared to previous arrhythmia detection system designs.

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Section: Review Of Literaturementioning

confidence: 99%

An Optimized FPGA Based System Design for the Arrhythmia Detection using ECG

C*,

S V

2019

IJITEE

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“…The distance measured of closest point on hyper-plane to origin can be found by maximizing the value of x as x on its hyper plane. Thus accordingly, for the other side points we have the similar scenario [14], [15].…”

Section: Fig 5: Morphological Segmentation On Character Analysismentioning

confidence: 99%

A morphological segmentation and curve-let features extraction on text region classification using SVM

Dey

Goswami

2015

2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)

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Text Extraction from different background is always a challenging problem in these emerging field of research area of image processing. In our project we have implemented upon Noise Removal segmentation, Curve-let Transformation features and Support Vector Machine classifier. In that we calculated on successful result purpose on still images and some real time images for different background location image on features extraction and classified techniques. Previously, Different methodologies have been used for texture feature extraction. The method which we proposed gives a better accuracy and efficiency towards extract texture feature analysis as with wavelet transform. Curve-let, Gradient Edge Operator on Support Vector Machine Classifier analysis and performance measure is completely new in this paper.

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“…These methods can lead to better results on the heterogeneous documents but they require a lot of a priori knowledge. The literature presents yet more recent approaches, which are more robust and less dependent on a priori knowledge, that are mainly based on the characterization of the document texture [16,17], the multi-scale analysis [18], the edge analysis [19],the grammatical model learning [20], the rules-based techniques [21] or the stochastic methods [22].Consequently, most of the proposed methods either require a priori knowledge related to the nature or the document structure, a high computing time and enormous resources, or they are not suitable for documents with potential defects and damages. In addition, most of the suggested works does not lead to an evaluation of their performances or to a comparison with other approaches.…”

Section: IImentioning

confidence: 99%

Image Extracting from Ancient Arab Documents with Complex Structures

Charrada¹

2014

IJCDS

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Text Region Extraction in a Document Image Based on Discrete Wavelet transforms

Cited by 14 publications

References 2 publications

An Optimized FPGA Based System Design for the Arrhythmia Detection using ECG

An Optimized FPGA Based System Design for the Arrhythmia Detection using ECG

A morphological segmentation and curve-let features extraction on text region classification using SVM

Image Extracting from Ancient Arab Documents with Complex Structures

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