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Moving target detection under turbulence degraded visible and infrared image sequences 1

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2nd international conference on computer vision and image processing, cvip 2017

作者： Veenu, Chaudhary Ajay, Kumar Anurekha, Sharma Department of Electronic Science Kurukshetra University KurukshetraHaryana136119 India Instrumentation Research and Development Establishment DehradunUttarakhand248008 India

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

The presence of atmospheric turbulence over horizontal imaging paths introduces time-varying perturbations and blur in the scene that severely degrade the performance of moving object detection and tracking systems of vision applications. This paper proposed a simple and efficient algorithm for moving target detection under turbulent media, based on adaptive background subtraction approach with different types of background models followed by adaptive global thresholding to detect foreground. This proposed method is implemented in MATLAB and tested on turbulence degraded video sequences. Further, this proposed method is also compared with state-of-the-art method published in the literature. The result shows that the detection performance by proposed algorithm is better. Further, the proposed method can be easily implemented in FPGA-based hardware. © 2018, Springer Nature Singapore Pte Ltd.

关键词： computer vision

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Embedded Home Surveillance System 19

Embedded Home Surveillance System

引用

19th international conference on computer and Information Technology (ICCIT)

作者： Ali, Shahnewaz

ISBN: (纸本)9781509040902

Video surveillance system is widely adopted in order to secure life. This paper presents embedded home surveillance systems to detect intruder in home environment. Proposed system works on embedded Linux board which is equipped with an ordinary web camera. At software level, it uses Open computer vision library to detect intruder in two different steps, Histogram of Oriented Gradient and Haar Like Features in association with Support Vector Machine. Moreover, it compares reference histogram to histogram of current image frame by using correlation methods and interpolates change of contents or light intensity in order to optimize the system in terms of false alarm minimization. Along with the Video server, Internet of Things application architecture has been adopted that provides remote monitoring. Alarm service, follows service oriented architecture;execute a set of predefined tasks such as alarming bell, turn on or off switches. This system provides a way to validate each camera module, able to detect device fault, examine image quality and image content changes. The system software provides an architectural solution for intelligent home surveillance system by incorporating computer vision and Digital image processing algorithms.

关键词： Embedded System computer vision Surveillance System Intruder Detection Service Oriented Architecture

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Autonomous Robust Helipad Detection Algorithm Using computer vision

Autonomous Robust Helipad Detection Algorithm Using Computer...

引用

international conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Prakash, R. Om Saravanan, Chandran Natl Inst Technol Durgapur Dept Comp Sci & Engn Durgapur India Natl Inst Technol Durgapur Ctr Comp Durgapur India

ISBN: (纸本)9781467399395

This paper presents the design and implementation of a vision based Helipad detection algorithm in an aerial image by image processing techniques. The aerial image obtained from the on board camera of Unmanned Aerial Vehicle (UAV) was processed by several image processing techniques to remove the noise and to segment the helipad. Then this image was matched with a pre-loaded template of the Helipad by means of Point Feature Matching by Speeded up Robust Features (SURF) thereby detecting the Helipad in the aerial image. This method is successful in detecting the Helipad in an aerial image irrespective of its scale change or in-plane rotation. It is also robust to small amount of out-of-plane rotation and occlusion. The average helipad detection time was found to be 28ms. This technique can be incorporated in embedded systems of the UAV's for autonomously detecting the Helipad for landing. We have presented the results tested on MATLAB (image processing Toolbox) which demonstrates that this helipad detection algorithm is robust.

关键词： helipad detection autonomous navigation SURF UAV computer vision

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Modelling the Scene Dependent Imaging in Cameras with a Deep Neural Network 16

Modelling the Scene Dependent Imaging in Cameras with a Deep...

引用

16th IEEE international conference on computer vision (ICCV)

作者： Nam, Seonghyeon Kim, Seon Joo Yonsei Univ Seoul South Korea

ISBN: (纸本)9781538610329

We present a novel deep learning framework that models the scene dependent image processing inside cameras. Often called as the radiometric calibration, the process of recovering RAW images from processed images (JPEG format in the sRGB color space) is essential for many computer vision tasks that rely on physically accurate radiance values. All previous works rely on the deterministic imaging model where the color transformation stays the same regardless of the scene and thus they can only be applied for images taken under the manual mode. In this paper, we propose a data-driven approach to learn the scene dependent and locally varying image processing inside cameras under the automode. Our method incorporates both the global and the local scene context into pixel-wise features via multi-scale pyramid of learnable histogram layers. The results show that we can model the imaging pipeline of different cameras that operate under the automode accurately in both directions (from RAW to sRGB, from sRGB to RAW) and we show how we can apply our method to improve the performance of image deblurring.

关键词： image color analysis Cameras Histograms Machine learning

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Visual deficiencies of digitized analog video-a study of a video home system (VHS) archive

Visual deficiencies of digitized analog video-a study of a v...

引用

2016 international conference on Interfaces and Human computer Interaction, IHCI 2016, Game and Entertainment Technologies, GET 2016 and computer Graphics, Visualization, computer vision and image processing, CGVcvip 2016

作者： Möller, Stefanie Eibl, Maximilian Technische Universität Chemnitz Germany

ISBN: (纸本)9789898533524

This paper contemplates first considerations about categorizing typical issues concerning the visual quality in digitized analog video. The basis of our study is analog archive material produced in the early 1990ies by German local TV stations that is stored on (S)VHS tapes. These tapes are now being digitized, stored for archive purposes and optimized for further usage, e.g. in nowadays produced documentaries. The categorization of quality issues is the starting point for a profound image optimization.

关键词： image reconstruction

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An Efficient Approach for Skin Lesion Segmentation Using Dermoscopic images: A Deep Learning Approach 5th

An Efficient Approach for Skin Lesion Segmentation Using Der...

引用

5th international conference on computer vision and image processing, cvip 2020

作者： Nampalle, Kishore Babu Raman, Balasubramanian Computer Science and Engineering Department Indian Institute of Technology Roorkee Roorkee India

ISBN: (纸本)9789811610851

Segmentation is a process of detecting boundaries of an object to extract the object of interest within a given image. There are different techniques like CT scan, MRI scan, X-ray scan, and so on those can be used to get these medical images. processing of these medical images is laborious because of variation in size and shape, and contrast. Hence, Skin lesion segmentation became a challenging task for researchers and dermatologists. The Segmentation of medical images plays a vital role in medical diagnosis and further treatment. Although there are many proposed image segmentation techniques, there is no perfect segmentation method that supports different datasets. This paper presents an efficient skin lesion segmentation model using a Convolutional Deconvolutional Neural Networks (CDNN). The proposed framework is developed based on Convolutional Neural Networks (CNN) by replacing the classification network with a segmentation network. The proposed model has used international Skin Imaging Collaboration (ISIC) 2017 challenging data set and PH2 dataset, and results are compared with State of Art models U-Net and SegNet. © 2021, Springer Nature Singapore Pte Ltd.

关键词： computerized tomography

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Degraded Document image Binarization Using Active Contour Model 1

引用

5th international conference on computer vision and image processing, cvip 2020

作者： Gupta, Deepika Bag, Soumen Dhanbad826004 India

ISBN: (数字)9789811610929

ISBN: (纸本)9789811610912

Document image binarization separates the foreground from background which is a very crucial pre-processing step in OCR. Accuracy of binarization immensely influences the accuracy of OCR. Various degradations like inadequate illumination, complex background, ink bleed, smear, etc. make binarization a challenging exercise. In this paper, we propose a novel method for binarization based on Active Contour Model (ACM) which is different from current thresholding techniques. Instead of calculating a global or local threshold value, it uses the energy-minimization concept of ACM to accomplish binarization. Background of the document image is estimated adaptively and then removed to handle noises in degraded documents. Active contour model is then applied to the image to get the binary output. Comprehensive experimentation has been completed effectively with benchmark DIBCO series datasets. A comparison with other existing methods verifies the efficiency of the proposed method. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Active contour model DIBCO Document image binarization Hybrid thresholding OCR

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Posture recognition in HINE exercises

Posture recognition in HINE exercises

引用

international conference on computer vision and image processing, cvip 2016

作者： Ansari, Abdul Fatir Roy, Partha Pratim Dogra, Debi Prosad Department of Civil Engineering IIT Roorkee Roorkee247667 India Department of Computer Science & Engineering IIT Roorkee Roorkee247667 India School of Electrical Sciences IIT Bhubaneswar Bhubaneswar751013 India

ISBN: (纸本)9789811021060

Pattern recognition, image and video processing based automatic or semi-automatic methodologies are widely used in healthcare services. Especially, image and video guided systems have successfully replaced various medical processes including physical examinations of the patients, analyzing physiological and bio-mechanical parameters, etc. Such systems are becoming popular because of their robustness and acceptability amongst the healthcare community. In this paper, we present an efficient way of infant’s posture recognition in a given video sequence of Hammersmith Infant Neurological Examinations (HINE). Our proposed methodology can be considered as a step forward in the process of automating HINE tests through computer assisted tools. We have tested our methodology with a large set of HINE videos recorded at the neuro-development clinic of hospital. It has been found that the proposed methodology can successfully classify the postures of infants with an accuracy of 78.26 %. © Springer Science+Business Media Singapore 2017.

关键词： Hidden Markov models

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Detection algorithm for copy-move forgery based on circle block

Detection algorithm for copy-move forgery based on circle bl...

引用

international conference on computer vision and image processing, cvip 2016

作者： Prakash, Choudhary Shyam Maheshkar, Sushila Department of Computer Science and Engineering Indian School of Mines Dhanbad India

ISBN: (纸本)9789811021060

Today lots of software tools are available which are used tomanipulate the images easily to change their originality. The technique which is usually used these days for tampering an image without leaving any microscopic evidence is copy-move forgery. There are many existing techniques to detect image tampering but their computational complexity is high. Here we present a robust and effective technique to find the tampered region. Initially the given image is divided into fixed size blocks and DCT is applied on each block for feature extraction. Circle is used to represent each transformed block with two feature vectors. In this way we reduce the dimension of the blocks to extract the feature vectors. Then lexicographical sort is applied to sort the extracted feature vectors. Matching algorithm is applied to detect the tampered regions. Results show that our algorithm is robust and has less computational complexity than the existing one. © Springer Science+Business Media Singapore 2017.

关键词： Computational complexity

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A Large Volume Natural Tamil Character Dataset 6th

A Large Volume Natural Tamil Character Dataset

引用

6th international conference on computer vision and image processing, cvip 2021

作者： Arun, M. Arivazhagan, S. Ahila Priyadharshini, R. Centre for Image Processing and Pattern Recognition Mepco Schlenk Engineering College Tamil Nadu Sivakasi India

ISBN: (纸本)9783031113451

This paper focuses on recognizing the individual Tamil characters in images of natural scenes. Even though natural character dataset are available publicly for different languages, no specific standardized dataset is available for natural Tamil characters. In this work, we present a publicly available Tamil character dataset "Mepco-TamNatChar" for natural Tamil character recognition. This research work presents the preliminary results on natural Tamil character recognition using spatial and machine learnt features. We report an accuracy of 87.50 ± 1.42% for a train test ratio of 50:50 using machine learnt features. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Character recognition

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