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Equalizing the amount of processing time for each reducer instead of equalizing the amount of data each process in heterogeneous environment. A lightweight strategy to address the data skew problem among the reductions of MapReduce applications. MapReduce has been widely used in various applications, including web indexing, log analysis, data mining, scientific simulations and machine translations. The data skew refers to the imbalance in the amount of data assigned to each task.Using an innovative sampling method which can achieve a highly accurate approximation to the distribution of the intermediate data by sampling only a small fraction during the map processing and to reduce the data in reducer side. Prioritizing the sampling tasks for partitioning decision and splitting of large keys is supported when application semantics permit.Thus providing a reduced data of total ordered output as a result by range partitioner. In the proposed system, the data reduction is by predicting the reduction orders in parallel data processing using feature and instance selection. The accuracy of the data scale and data skew is effectively improved by CHI-ICF data reduction technique. In the existing system normal data distribution is calculated instead here still efficient distribution of data using the feature selection by χ 2 statistics (CHI) and instance selection by Iterative case filter (ICF) is processed.Data Dimensional Reduction by Order Prediction in Heterogeneous Environment
Data Dimensional Reduction by Order Prediction in Heterogeneous EnvironmentAssociation of Scientists, Developers and Faculties
This paper presents the development of a camera-based assistive text reading framework to help blind persons read text labels and product packaging from hand-held objects in their daily lives. Recent developments in computer vision, digital cameras, and portable computers make it feasible to assist these individuals by developing camera-based products that combine computer vision technology with other existing commercial products such optical character recognition (OCR) systems. To automatically extract the text regions from the object, we propose a artificial neural network algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized text regions are binarized for processing the algorithm and the text characters are recognized by off-the-shelf OCR (Optical Character Recognition) and other process involved . Now the binarized signals are converted to audible signal. The working principle is as follows first the respected image will be captured and then it is converted to binary signals. Now the image is diagnosed to find whether the text is present in the image. Secondly, if the text is present, then the object of interest is detected. The respected text of the image is recognized and then converted to audible signals. Thus the recognized text codes are given as speech to the user.A Robust Embedded Based String Recognition for Visually Impaired People
A Robust Embedded Based String Recognition for Visually Impaired PeopleAssociation of Scientists, Developers and Faculties
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Equalizing the amount of processing time for each reducer instead of equalizing the amount of data each process in heterogeneous environment. A lightweight strategy to address the data skew problem among the reductions of MapReduce applications. MapReduce has been widely used in various applications, including web indexing, log analysis, data mining, scientific simulations and machine translations. The data skew refers to the imbalance in the amount of data assigned to each task.Using an innovative sampling method which can achieve a highly accurate approximation to the distribution of the intermediate data by sampling only a small fraction during the map processing and to reduce the data in reducer side. Prioritizing the sampling tasks for partitioning decision and splitting of large keys is supported when application semantics permit.Thus providing a reduced data of total ordered output as a result by range partitioner. In the proposed system, the data reduction is by predicting the reduction orders in parallel data processing using feature and instance selection. The accuracy of the data scale and data skew is effectively improved by CHI-ICF data reduction technique. In the existing system normal data distribution is calculated instead here still efficient distribution of data using the feature selection by χ 2 statistics (CHI) and instance selection by Iterative case filter (ICF) is processed.Data Dimensional Reduction by Order Prediction in Heterogeneous Environment
Data Dimensional Reduction by Order Prediction in Heterogeneous EnvironmentAssociation of Scientists, Developers and Faculties
This paper presents the development of a camera-based assistive text reading framework to help blind persons read text labels and product packaging from hand-held objects in their daily lives. Recent developments in computer vision, digital cameras, and portable computers make it feasible to assist these individuals by developing camera-based products that combine computer vision technology with other existing commercial products such optical character recognition (OCR) systems. To automatically extract the text regions from the object, we propose a artificial neural network algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized text regions are binarized for processing the algorithm and the text characters are recognized by off-the-shelf OCR (Optical Character Recognition) and other process involved . Now the binarized signals are converted to audible signal. The working principle is as follows first the respected image will be captured and then it is converted to binary signals. Now the image is diagnosed to find whether the text is present in the image. Secondly, if the text is present, then the object of interest is detected. The respected text of the image is recognized and then converted to audible signals. Thus the recognized text codes are given as speech to the user.A Robust Embedded Based String Recognition for Visually Impaired People
A Robust Embedded Based String Recognition for Visually Impaired PeopleAssociation of Scientists, Developers and Faculties