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Convolutional Neural Network Training with Artificial Pattern for Bangla Handwritten Numeral Recognition

Convolutional Neural Network Training with Artificial Patter...

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international conference on Informatics, Electronics and vision

作者： M. A. H. Akhand Mahtab Ahmed M. M. Hafizur Rahman Dept. of Computer Science and Engineering Khulna University of Engineering & Technology Dept. of Computer Science KICT International Islamic University Malaysia

ISBN: (纸本)9781509012701

Recognition of handwritten numerals has gained much interest in recent years due to its various application potentials. The progress of handwritten Bangla numeral is well behind Roman, Chinese and Arabic scripts although it is a major language in Indian subcontinent and is the first language of Bangladesh. Handwritten numeral classification is a high-dimensional complex task and existing methods use distinct feature extraction techniques and various classification tools in their recognition schemes. Recently, convolutional neural network (CNN) is found efficient for image classification with its distinct features. In this study, a CNN based method has been investigated for Bangla handwritten numeral recognition. A moderated pre-processing has been adopted to produce patterns from handwritten scan images. On the other hand, CNN has been trained with the patterns plus a number of artificial patterns. A simple rotation based approach is employed to generate artificial patterns. The proposed CNN with artificial pattern is shown to outperform other existing methods while tested on a popular Bangla benchmark handwritten dataset.

关键词： Bangla Numeral Convolutional Neural Network Pattern Generation Handwritten Numeral Recognition

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Measurement of the Zone of Inhibition of an Antibiotic

Measurement of the Zone of Inhibition of an Antibiotic

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IEEE international Advance Computing conference, IACC

作者： H.S. Bhargav Sachin D. Shastri S.P. Poornav K.M. Darshan Mahendra M. Nayak Department of Computer Science and Engineering PES Institute of Technology Bangalore India Dept. of Electrical and Electronics Engineering PES Institute of Technology Bangalore India

In the Disk Diffusion Antibiotic Sensitivity test (The Kirby-Bauer test) a thin film of bacteria applied on a plate is subjected to various antibiotics. The Zone of inhibition is a circular area around the spot of the antibiotic in which the bacteria colonies do not grow. The zone of inhibition can be used to measure the susceptibility of the bacteria to wards the antibiotic. The process of measuring the diameter of this Zone of Inhibition can be automated using image processing. In this work an algorithm is developed, using computer vision, which will detect the zones of inhibition of the bacteria. This work demonstrates an effective approach of measuring the Zone of Inhibition by calculating the radius of the zone by drawing contours and setting the right value of threshold. This work also determines if a particular bacteria is susceptible or resistant to the applied antibiotic using the calculated Zone of Inhibition and the prescribed standard values.

关键词： Antibiotics Microorganisms Mathematical model Gray-scale Standards image edge detection

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Open source digital camera on field programmable gate arrays

Open source digital camera on field programmable gate arrays

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IEEE international conference on Electro-Information Technology

作者： Cristinel Ababei Shaun Duerr Joe Ebel Russell Marineau Milad Ghorbani Moghaddam Tanzania Sewell Department of Electrical and Computer Engineering Marquette University Milwaukee WI USA

ISBN: (纸本)9781467399869

We present an open source digital camera implemented on a field programmable gate array (FPGA). The camera functionality is completely described in VHDL and tested on the DE2-115 educational FPGA board. Some of the current features of the camera include video mode at 30 fps, storage of taken snapshots into SDRAM memories, and grayscale and edge detection filters. The main contributions of this project include 1) the actual system level design of the camera, tested and verified on an actual FPGA chip, and 2) the public release of the entire implementation including source code and documentation. While the proposed camera is far from being able to compete with commercial offerings, it can serve as a framework to test new research ideas related to digital camera systems, image processing, computer vision, etc., as well as an educational platform for advanced digital design with VHDL and FPGAs.

关键词： Field programmable gate arrays Gray-scale Digital cameras image edge detection SDRAM

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A novel saliency detection model based on curvelet transform

A novel saliency detection model based on curvelet transform

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international conference on Wireless Communications and Signal processing (WCSP)

作者： Peiqing Bai Ziguan Cui Zongliang Gan Guijin Tang Feng Liu Image Processing & Image Communication Lab Nanjing University of Posts & Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts & Telecommunications Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781509028610

Visually salient object or region detection in images is an active research field in recent years. Inspired by that curvelets can provide multi-scale sparse representation of objects with edges and textures, in this paper, we propose a novel saliency detection model based on fast discrete curvelet transform (SDCT) to detect more compact salient objects in an image. First, fast discrete curvelet transform is used to acquire multi-scale representation of feature maps in CIELab color space. Then the feature maps are transformed to feature salient maps based on dissimilarity measure between patches in a global manner. Finally, the complementary feature salient maps at each scale and each color channel are merged linearly to obtain unitary saliency map. Experimental results on MSRA saliency benchmark database show that the proposed SDCT model outperforms the most state-of-the-art saliency detection models in spatial and frequency domain with higher overall performance, especially acquires more compact salient object and suppresses background saliency effectively, which is desirable for many computer vision applications.

关键词： Transforms Feature extraction image color analysis Frequency-domain analysis Computational modeling Visualization image edge detection

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Weighted Mean Filter for removal of high density Salt and Pepper noise

Weighted Mean Filter for removal of high density Salt and Pe...

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international conference on Advanced Computing and Communication Systems (ICACCS)

作者： Neela Chithirala Natasha B. Rubini N. Anisha Radhakrishnan Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham University Coimbatore India Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu IN Amrita Vishwa Vidyapeetham University

ISBN: (纸本)9781467392075

The essential constraint on the input images to any computer vision technology is its quality. Acquiring noise free digital images is a challenge as it depends on several factors. Developing algorithms to remove noise is one way to improve the image quality. Salt and pepper noise degrades the image. The challenge here is to restore the lost information without distorting the edges. This paper introduces a new algorithm that reduces high density salt and pepper noise from images. Restoration is done by calculating the weighted mean of the nearby pixels. Weights are assigned unsymmetrically to pre-processed and unprocessed pixels. The quality was judged based on the PSNR value. The algorithm restores information for highly corrupted images. Salt and pepper noise are usually filtered with variants of the median filter. This paper provides an alternate way for noise reduction.

关键词： Filtering algorithms Communication systems Signal processing algorithms image edge detection Information filters Noise measurement

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Identifying exudates from diabetic retinopathy images

Identifying exudates from diabetic retinopathy images

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international conference on Advanced Communication, Control and Computing Technologies (ICACCCT)

作者： A. Sindhura S. Deva Kumar V Ramakrishna Sajja N Gnaneswara Rao Computer Science & Engineering Department VFSTR University Andhra Pradesh India

ISBN: (纸本)9781467395465

Diabetic Retinopathy (DR) is the problem for long-standing diabetes and the major cause for visual loss is because of variations in blood vessels of the retina. vision loss is due to DR is preventable with regular checkups at the earlier stages. The presence of exudates is the basic signs of DR. Hence, exudates detection becomes a major problem-solving task, in which retinal images plays a vital role. In this paper, a technique is proposed depending on morphological closing operations which are in image processing is used to identify exudates from retinal image. At the starting phase, the retinal image must be preprocessed, where at first the image which is in RGB color format is altered to the image of HSI color format and on Intensity-band of HSI color format average filter is performed to reduce noise and subsequently contrast-limited adaptive histogram equalization is performed to normalize the image. In subsequent phase, exudates are identified using morphological closing operation and then Nilblack's thresholding is applied. On comparing the results, the proposed technique got better performance than the existing technique.

关键词： Retina Histograms image color analysis Diabetes image segmentation Low-pass filters Adaptive equalizers

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Welding seam detection and feature point extraction for robotic arc welding using laser-vision

Welding seam detection and feature point extraction for robo...

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international conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Jun-Di Sun Guang-Zhong Cao Su-Dan Huang Ken Chen Jun-Jun Yang Shenzhen Key Laboratory of Electromagnetic Control Shenzhen University Shenzhen China Department of Electrical Engineering Southwest Jiaotong University Chengdu Sichuan China

ISBN: (纸本)9781509008223

A welding seam detection and feature point extraction system for robotic arc welding is proposed in this paper. The system consists of a CCD camera, a line structure laser, a narrowband optical filter to overcome the interference from arc light and other light sources, and an embedded computer board for image processing and error calculation. By taking use of optical triangulation measurement method, the welding seam positions of cross direction and vertical direction can be measured from the feature points' positions of the welding seam in captured images. Advanced image processing algorithms are developed and implemented on the embedded computer board to process the images captured by the camera. Laser stripe region is defined from the entire image, and the effects of bright spots on the images caused by spatters and reflection are eliminated by area-size filtering algorithm. In order to detect the feature points, an algorithm based on the second order difference of the column indexes of the pixels on the laser stripe is implemented. Experiments results show that the measurement errors in cross direction and vertical direction are within the range of 0.5mm and 1.0mm respectively, which can meet the demands of accuracy for welding seam detection. The processing speed of the system is about 20 images per second, which can meet the demands of speed for arc welding robot.

关键词： Welding Laser theory Real-time systems computers Robots

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Improving the color image segmentation using fuzzy-C-means

Improving the color image segmentation using fuzzy-C-means

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international conference on Advanced Communication, Control and Computing Technologies (ICACCCT)

作者： Balpreet Kaur Prabhpreet Kaur Department of Computer Engineering & Technology Guru Nanak Dev University Amritsar Punjab INDIA

ISBN: (纸本)9781467395465

image segmentation is found to be critical issue in vision processing. Segmenting the images in more proficient manner is still a challenging issue. Many techniques has been proposed so far, but no one is effective for a particular kind of image. The comprehensive review has shown that the use of fuzzy enhancement is not considered in gray stretch based method. The existing technique provides poor results for complex background images. The effect of color images on segmentation is also ignored. The disadvantage of threshold based segmentation technique is that it can perform well for images, which contain only two components. Otsu's method fails to calculate accurate threshold value when there is no significant change in the gray level of pixels. Therefore in this paper a fuzzy c means clustering technique is proposed for obtaining effective results for complex background images. The comparisons have clearly shown the effectiveness of the proposed technique.

关键词： image segmentation Discrete wavelet transforms Clustering algorithms Mean square error methods computers Digital images

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Saliency Optimization Based on Compactness and Background-Prior

Saliency Optimization Based on Compactness and Background-Pr...

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Yu Zheng Lu Li Xiangzhi Bai Fugen Zhou Image Processing Center Beihang University Beijing China

Saliency detection has drawn increasing attention in the communities of computer vision and image processing. Recently, foreground compactness and background prior have been developed to enhance saliency detection. In this paper, we propose an effective saliency optimization scheme taking account the foreground compactness and background prior. First, a foreground compactness-based saliency detection algorithm is introduced, which integrates the center contrast and the compactness-fused representation of the Gaussian Mixture Models (GMMs)-decomposed soft abstraction. Second, a foreground-based background seeds selection algorithm is proposed to obtain the enhanced background prior based saliency, which can well alleviate the influence of the on-boundary objects to the final saliency in conventional background prior based saliency algorithms. At last, the problem of compactness and background prior-based saliency integration is formulated as a multi-objective optimization problem to obtain the optimal saliency. Extensive experiments on ASD and MSRA10K database demonstrate that the proposed method outperforms the state-of-the -art saliency detection methods.

关键词： image color analysis Clustering algorithms Cost function Classification algorithms Fingerprint recognition

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Real-time Gestural Interface for Navigation in Virtual Environment

Real-time Gestural Interface for Navigation in Virtual Envir...

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international conference on Development and Application Systems

作者： Oana-Mihaela Vultur Stefan-Gheorghe Pentiuc Valeriu Lupu Stefan cel Mare University of Suceava Suceava Romania Faculty of Electrical Engineering and Computer Science MintViz Lab MANSiD Research Center Stefan cel Mare University of Suceava Romania Faculty of Economics and Public Administration Stefan cel Mare University of Suceava Suceava Romania

ISBN: (纸本)9781509019946

Human computer Interaction (HCI) is a challenging domain that has changed and proposed many user experience paradigms. In this paper we will try to present a innovative gestural interface that allows users to navigate in a virtual environment, representing the Rectorat building of the "Stefan cel Mare" University of Suceava, using dynamic gestures. In this fully natural interface the human body is the controller. We designed an interface for human gesture recognition based on the sets of the coordinates of human joints transmitted by a Microsoft Kinect sensor to the computer. The virtual reality system and the gestural recognition module are running on the computer. The human movements are supervised continuously and if a gesture is recognized the corresponding command is transmitted to the VR system. We also made a performance analysis of the gestural interface. The evaluation has been focused on the accuracy of the gesture recognition process and on the degree of user satisfaction after experimenting such interaction with VR system.

关键词： Human-computer Interaction (HCI) image processing computer vision gesture recognition

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