Comparison of Articles on Content Based Image Retrieval
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Comparison between Content –Based Image Retrieval Based on Electromagnetism-Like Mechanism” on Hindawi Publishing Corporation, Mathematical Problems in Engineering Volume 2013 available on http://dx.doi.org/10.1155/2013/782519 and Content Based Image Retrieval using Exact Legendre Moments and Support Vector Machine on The International Journal of Multimedia and Its Application Volume 2, No.2, May 2010.
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1) The document proposes analog signal processing as a solution to reduce computation time for image alignment algorithms that have high computational loads.
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A NOVEL IMAGE SEGMENTATION ENHANCEMENT TECHNIQUE BASED ON ACTIVE CONTOUR AND...
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Biomedical Image Retrieval using LBWP
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Research Inventy : International Journal of Engineering and Science
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Volume 2-issue-6-1974-1978
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A METHODICAL WAY OF IMAGE REGISTRATION IN DIGITAL IMAGE PROCESSING
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Image registration is the fundamental task used to
match two or more partially overlapping images taken, for
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different viewpoints and stitch these images into one
panoramic image comprising the whole scene. It is
afundamental image processing technique and is very useful
in integrating information from different sensors, finding
changes in images taken at different times, inferring threedimensional
information from stereo images, and recognizing
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registration problem. The purpose of this paper is to present a
survey of image registration techniques. This technique of
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images are reference image and sensed image. The ultimate
purpose of digital image filtering is to support the visual
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A Hybrid Approach for Content Based Image Retrieval System
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IRJET- Fusion based Brain Tumor Detection
1. The document discusses a method for detecting brain tumors using medical image fusion and support vector machines (SVM).
2. It involves fusing two MRI images using SVM to create a single fused image with more information than the original images. Texture and wavelet features are then extracted from the fused image.
3. The SVM classifier classifies the brain tumors as benign or malignant based on the trained and tested features extracted from the fused image.
OBJECT DETECTION, EXTRACTION AND CLASSIFICATION USING IMAGE PROCESSING TECHNIQUE
OBJECT DETECTION, EXTRACTION AND CLASSIFICATION USING IMAGE PROCESSING TECHNIQUEJournal For Research
Domestic refrigerators are widely used household appliances and a large extent of energy is consumed by this system. A phase change material is a substances that can store or release significant amount of heat energy by changing the phase liquid to vapour or vice versa. So, reduction of temperature fluctuation and improvement of system performances is that main reason of using PCM enhances the heat transfer rate thus improves the COP of refrigeration as well as the quality frozen food. The release and storage rate of a refrigerator is depends upon the characteristics of refrigerators and its properties using phase change material for a certain thermal load it is found that COP of conventional refrigerator is increased . The phase change material used in chamber built manually and which surrounds the evaporator chamber of a conventional refrigerator the whole heat transfer for load given to refrigerator cabin (to evaporator) evaporator to phase change material by conduction. This system hence improves the performances of household refrigerator by increasing its compressor cut-off time and thereby minimizing electrical energy usage. The main objective is to improve the performance, cooling time period, storage capacity and to maintain the constant cooling effect for more time during power cut off hours using phase change material.Image Fusion and Image Quality Assessment of Fused Images
Accurate diagnosis of tumor extent is important in radiotherapy. This paper presents the use of image fusion of PET and MRI image. Multi-sensor image fusion is the process of combining information from two or more images into a single image. The resulting image contains more information as compared to individual images. PET delivers high-resolution molecular imaging with a resolution down to 2.5 mm full width at half maximum (FWHM), which allows us to observe the brain\'s molecular changes using the specific reporter genes and probes. On the other hand, the 7.0 T-MRI, with sub-millimeter resolution images of the cortical areas down to 250 m, allows us to visualize the fine details of the brainstem areas as well as the many cortical and sub-cortical areas. The PET-MRI fusion imaging system provides complete information on neurological diseases as well as cognitive neurosciences. The paper presents PCA based image fusion and also focuses on image fusion algorithm based on wavelet transform to improve resolution of the images in which two images to be fused are firstly decomposed into sub-images with different frequency and then the information fusion is performed and finally these sub-images are reconstructed into result image with plentiful information. . We also propose image fusion in Radon space. This paper presents assessment of image fusion by measuring the quantity of enhanced information in fused images. We use entropy, mean, standard deviation and Fusion Mutual Information, cross correlation , Mutual Information Root Mean Square Error, Universal Image Quality Index and Relative shift in mean to compare fused image quality. Comparative evaluation of fused images is a critical step to evaluate the relative performance of different image fusion algorithms. In this paper, we also propose image quality metric based on the human vision system (HVS).
IRJET- Art Authentication System using Deep Neural Networks
1) The document presents a system to authenticate paintings by artists using deep convolutional neural networks. The system processes images through thousands of neurons to extract patterns and characteristics of an artist's style.
2) A deep convolutional neural network model is implemented and trained on datasets of labeled artworks. The network aims to classify new paintings by artist with 80% accuracy, higher than previous methods.
3) The system was tested on 5 paintings, with a confusion matrix showing correct and incorrect classifications. The 80% accuracy rate is an improvement over previous techniques, but the model has limitations as the number of paintings increases.
Evaluation powerpoint comparison
In contrast, "Route of the eye" uses an informal language and focuses on visuals with double page spreads, multiple images and boxed out text. It emphasizes visual storytelling over traditional magazine conventions.
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Ijetcas14 329
This document presents a novel iris recognition technique that uses fractional energies of transformed iris images to extract features and identify individuals. Various transforms like cosine, Walsh, Haar, Kekre, and Hartley transforms are applied to iris images to generate transformed images. Feature vectors are then extracted from the transformed images by selecting the higher energy coefficients, which represent most of the image information. Performance is evaluated using genuine acceptance rate on different percentages of higher energies, from 100% down to 96%. The technique is tested on a database of 384 iris images from 64 individuals. Results show that cosine and Walsh transforms achieve the best genuine acceptance rate of 85% when using 99% of the fractional energies. Considering fractional energies improves performance by reducing computations compared to
Volume 2-issue-6-1974-1978
This document discusses content-based image mining techniques for image retrieval. It provides an overview of image mining, describing how image mining goes beyond content-based image retrieval by aiming to discover significant patterns in large image collections according to user queries. The document reviews several existing image mining techniques, including those using color histograms, texture analysis, clustering algorithms like k-means, and association rule mining. It discusses challenges in developing universal image retrieval methods and proposes combining low-level visual features with high-level semantic features. Overall, the document surveys the state of the art in content-based image mining and retrieval.
A METHODICAL WAY OF IMAGE REGISTRATION IN DIGITAL IMAGE PROCESSING
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Image registration is the fundamental task used to
match two or more partially overlapping images taken, for
example, at different times,from different sensors, or from
different viewpoints and stitch these images into one
panoramic image comprising the whole scene. It is
afundamental image processing technique and is very useful
in integrating information from different sensors, finding
changes in images taken at different times, inferring threedimensional
information from stereo images, and recognizing
model-based objects.
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registration problem. The purpose of this paper is to present a
survey of image registration techniques. This technique of
image registration aligns two images geometrically. These two
images are reference image and sensed image. The ultimate
purpose of digital image filtering is to support the visual
identification of certain features expressed by characteristic
shapes and patterns. Numerous recipes, algorithms and ready
made programs exist nowadays that predominantly have in
common that users have to set certain parameters.
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immediately, the choice of parameters may be guided by
making the image ―looking nice‖. However, in practical
situations most users are not in a mood to ―play around‖
with a displayed image, particularly if they are in a stressy
situation as it may encountered in security applications. The
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06 17443 an neuro fuzzy...
Image fusion is a sub field of image processing in which more than one images are fused to create an image where all the objects are in focus. The process of image fusion is performed for multi-sensor and multi-focus images of the same scene. Multi-sensor images of the same scene are captured by different sensors whereas multi-focus images are captured by the same sensor. In multi-focus images, the objects in the scene which are closer to the camera are in focus and the farther objects get blurred. Contrary to it, when the farther objects are focused then closer objects get blurred in the image. To achieve an image where all the objects are in focus, the process of images fusion is performed either in spatial domain or in transformed domain. In recent times, the applications of image processing have grown immensely. Usually due to limited depth of field of optical lenses especially with greater focal length, it becomes impossible to obtain an image where all the objects are in focus. Thus, it plays an important role to perform other tasks of image processing such as image segmentation, edge detection, stereo matching and image enhancement. Hence, a novel feature-level multi-focus image fusion technique has been proposed which fuses multi-focus images. Thus, the results of extensive experimentation performed to highlight the efficiency and utility of the proposed technique is presented. The proposed work further explores comparison between fuzzy based image fusion and neuro fuzzy fusion technique along with quality evaluation indices.
Balancing Compression and Encryption of Satellite Imagery
With the rapid developments in the remote sensing technologies and services, there is a necessity for combined compression and encryption of satellite imagery. The onboard satellite compression is used to minimize storage and communication bandwidth requirements of high data rate satellite applications. While encryption is employed to secure these resources and prevent illegal use of image sensitive information. In this paper, we propose an approach to address these challenges which raised in the highly dynamic satellite based networked environment. This approach combined compression algorithms (Huffman and SPIHT) and encryptions algorithms (RC4, blowfish and AES) into three complementary modes: (1) secure lossless compression, (2) secure lossy compression and (3) secure hybrid compression. The extensive experiments on the 126 satellite images dataset showed that our approach outperforms traditional and state of art approaches by saving approximately (53%) of computational resources. In addition, the interesting feature of this approach is these three options that mimic reality by imposing every time a different approach to deal with the problem of limited computing and communication resources.
A Hybrid Approach for Content Based Image Retrieval System
This document describes a hybrid approach for content-based image retrieval. It combines several spatial features - row sum, column sum, forward and backward diagonal sums - and histograms to represent images with feature vectors. Euclidean distance is used to calculate similarity between a query image's feature vector and those in the database. The approach is evaluated using precision-recall calculations on different image groups, showing the hybrid method performs best by combining multiple features.
A Large-scale hierarchical image database
The digital era has brought with it an enormous explosion of data.
More robust models and algorithms can be proposed by exploiting these images.
How such data can be utilized and organized ?
In this paper, introduce a new image database called “ImageNet”.
Solution for intra/inter-cluster event-reporting problem in cluster-based pro...
In recent years, wireless sensor networks (WSNs) have been considered one of the important topics for researchers due to their wide applications in our life. Several researches have been conducted to improve WSNs performance and solve their issues. One of these issues is the energy limitation in WSNs since the source of energy in most WSNs is the battery. Accordingly, various protocols and techniques have been proposed with the intention of reducing power consumption of WSNs and lengthen their lifetime. Cluster-oriented routing protocols are one of the most effective categories of these protocols. In this article, we consider a major issue affecting the performance of this category of protocols, which we call the intra/inter-cluster event-reporting problem (IICERP). We demonstrate that IICERP severely reduces the performance of a cluster-oriented routing protocol, so we suggest an effective Solution for IICERP (SIICERP). To assess SIICERP’s performance, comprehensive simulations were performed to demonstrate the performance of several cluster-oriented protocols without and with SIICERP. Simulation results revealed that SIICERP substantially increases the performance of cluster-oriented routing protocols.
IRJET - Symmetric Image Registration based on Intensity and Spatial Informati...
This document presents a proposed system for symmetric image registration based on intensity and spatial information using a technique called the Coloured Simple Algebraic Algorithm (CSAA). The system first preprocesses color images, extracts features, then classifies images as symmetric or asymmetric using a neural network. It is shown to provide accurate and robust registration of medical and biomedical images. The system is implemented and evaluated on sample images, demonstrating it can successfully identify symmetric versus asymmetric images. The proposed approach aims to improve on existing techniques for intensity-based image registration tasks.
Efficient Database Management System For Wireless Sensor Network
An effective database management system has been put forward in this work to tackle the problem in remote monitoring using Wireless Sensor Network Object Oriented Analysis and Design method employed as classes was evolved to create objects in the employed program used. An algorithm was developed with a corresponding flowchart to realize the design, the work also came up with a dynamic graph plotter, as this offers an adaptive monitoring facility for data stored in the Database. Sensor Node query was implemented and result of transmitted data was filtered for a particular node
Mobile based Automated Complete Blood Count (Auto-CBC) Analysis System from B...
Blood cells diagnosis is becoming essential to ensure a proper treatment can be proposed to a blood related disease patient. In current research trending, automated complete blood count analysis system is required for pathologists or researchers to count the blood cells from the blood smeared images. Hence, a portable mobile-based complete blood count (CBC) analysis framework with the aid of microscope is proposed, and the smartphone camera is mounted to the viewing port of the light microscope by adding a smartphone support. Initially, the blood smeared image is acquired from a light microscope with objective zoom of 100X magnifications view the eyepiece zoom of 10X magnification, then captured by the smartphone camera. Next, the areas constitute to the WBC and RBC are extracted using combination of color space analysis, threshold and Otsu procedure. Then, the number of corresponding cells are counted using topological structural analysis, and the cells in clumped region is estimated using Hough Circle Transform (HCT) procedure. After that, the analysis results are saved in the database, and shown in the user interface of the smartphone application. Experimental results show the developed system can gain 92.93% accuracy for counting the RBC whereas 100% for counting the WBC.
IRJET- Fusion based Brain Tumor Detection
1. The document discusses a method for detecting brain tumors using medical image fusion and support vector machines (SVM).
2. It involves fusing two MRI images using SVM to create a single fused image with more information than the original images. Texture and wavelet features are then extracted from the fused image.
3. The SVM classifier classifies the brain tumors as benign or malignant based on the trained and tested features extracted from the fused image.
OBJECT DETECTION, EXTRACTION AND CLASSIFICATION USING IMAGE PROCESSING TECHNIQUE
OBJECT DETECTION, EXTRACTION AND CLASSIFICATION USING IMAGE PROCESSING TECHNIQUEJournal For Research
Domestic refrigerators are widely used household appliances and a large extent of energy is consumed by this system. A phase change material is a substances that can store or release significant amount of heat energy by changing the phase liquid to vapour or vice versa. So, reduction of temperature fluctuation and improvement of system performances is that main reason of using PCM enhances the heat transfer rate thus improves the COP of refrigeration as well as the quality frozen food. The release and storage rate of a refrigerator is depends upon the characteristics of refrigerators and its properties using phase change material for a certain thermal load it is found that COP of conventional refrigerator is increased . The phase change material used in chamber built manually and which surrounds the evaporator chamber of a conventional refrigerator the whole heat transfer for load given to refrigerator cabin (to evaporator) evaporator to phase change material by conduction. This system hence improves the performances of household refrigerator by increasing its compressor cut-off time and thereby minimizing electrical energy usage. The main objective is to improve the performance, cooling time period, storage capacity and to maintain the constant cooling effect for more time during power cut off hours using phase change material.Image Fusion and Image Quality Assessment of Fused Images
Accurate diagnosis of tumor extent is important in radiotherapy. This paper presents the use of image fusion of PET and MRI image. Multi-sensor image fusion is the process of combining information from two or more images into a single image. The resulting image contains more information as compared to individual images. PET delivers high-resolution molecular imaging with a resolution down to 2.5 mm full width at half maximum (FWHM), which allows us to observe the brain\'s molecular changes using the specific reporter genes and probes. On the other hand, the 7.0 T-MRI, with sub-millimeter resolution images of the cortical areas down to 250 m, allows us to visualize the fine details of the brainstem areas as well as the many cortical and sub-cortical areas. The PET-MRI fusion imaging system provides complete information on neurological diseases as well as cognitive neurosciences. The paper presents PCA based image fusion and also focuses on image fusion algorithm based on wavelet transform to improve resolution of the images in which two images to be fused are firstly decomposed into sub-images with different frequency and then the information fusion is performed and finally these sub-images are reconstructed into result image with plentiful information. . We also propose image fusion in Radon space. This paper presents assessment of image fusion by measuring the quantity of enhanced information in fused images. We use entropy, mean, standard deviation and Fusion Mutual Information, cross correlation , Mutual Information Root Mean Square Error, Universal Image Quality Index and Relative shift in mean to compare fused image quality. Comparative evaluation of fused images is a critical step to evaluate the relative performance of different image fusion algorithms. In this paper, we also propose image quality metric based on the human vision system (HVS).
IRJET- Art Authentication System using Deep Neural Networks
1) The document presents a system to authenticate paintings by artists using deep convolutional neural networks. The system processes images through thousands of neurons to extract patterns and characteristics of an artist's style.
2) A deep convolutional neural network model is implemented and trained on datasets of labeled artworks. The network aims to classify new paintings by artist with 80% accuracy, higher than previous methods.
3) The system was tested on 5 paintings, with a confusion matrix showing correct and incorrect classifications. The 80% accuracy rate is an improvement over previous techniques, but the model has limitations as the number of paintings increases.
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2015 Font Trends For Presentations
Goodbye boring old presentation fonts! Typography is one of the most important components of great PowerPoint design, and in 2015 rich typography will continue to be a dominating design element. Given that high quality fonts are more accessible and more affordable (often times FREE), be prepared to see some new, exciting and interesting trends in fonts within PowerPoint presentations. Interested in knowing more about presentation font trends in the upcoming year? Then, check out this presentation!
10 PowerPoint Templates That Don't Suck
Having a cool PowerPoint template is CRITICAL if you want to have slides that will WOW an audience. The benefits of purchasing a professional presentation template include:
Save Time – With a purchased template you can focus more on honing your message and less on building a template framework.
Elegant Design – The presentation templates are clean, minimal, and look professional.
Customizable – All the templates are easy to customize. Simply add your text and swap out any images/graphics you don’t want.
Customer Support – If you ever have any questions about the PowerPoint template you can leave a comment and the person who designed the template will get back to you fairly quickly.
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Animations Included – For many of the PowerPoint templates offered, there are custom animations built into the template. If you don’t want the animations you can always remove them.
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Similar to Comparison of Articles on Content Based Image Retrieval
META-HEURISTICS BASED ARF OPTIMIZATION FOR IMAGE RETRIEVAL
The document proposes an approach combining automatic relevance feedback and particle swarm optimization for image retrieval. It constructs a visual feature database from image features like color moments and Gabor filters. For a query image, it retrieves similar images and generates automatic relevance feedback by labeling images as relevant or irrelevant. It then uses particle swarm optimization to re-weight features and retrieve more relevant images over multiple iterations, splitting the swarm in later iterations. An experiment on Corel images over 5 classes showed the approach could effectively retrieve relevant images through this meta-heuristic process without human interaction.
Extended Performance Appraise of Image Retrieval Using the Feature Vector as ...
This document summarizes the results of testing an image retrieval technique that uses row means of transformed image columns as a feature vector on a database of 1000 images across 11 categories. Seven different transforms were tested, including DCT, DST, Haar, Walsh, Kekre, Slant, and Hartley. For each transform, precision and recall were calculated with and without including the DC component in the feature vector. The technique was tested on both gray and color versions of the database. In general, the technique produced higher precision and recall than using the full transform or simple row means, especially when including the DC component. For gray images, the best performing transforms were DST, Haar, Hartley, DCT,
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nternational Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Medical Image Processing � Detection of Cancer Brain
The primary notion relying in image processing is image segmentation and classification. The intention behind the processing is to originate the image into regions. Variation formulations that effect in valuable algorithms comprise the essential attributes of its region and boundaries. Works have been carried out both in continuous and discrete formulations, though discrete version of image segmentation does not approximate continuous formulation. An existing work presented unsupervised graph cut method for image processing which leads to segmentation inaccuracy and less flexibility. To enhance the process, our first work describes the process of formation of kernel for the medical images by performing the deviation of mapped image data within the scope of each region. But the segmentation of image is not so effective based on the regions present in the given medical image. To overcome the issue, we implement a Bayesian classifier as our second work to classify the image effectively. The segmented image classification is done based on its classes and processes using Bayesian classifiers. With the classified image, it is necessary to identify the objects present in the image. For that, in this work, we exploit the use of sequential pattern matching algorithm to identify the feature space of the objects in the classified image that are highly of important that improves the speed and accuracy rate in a significant manner. An experimental evaluation is carried out to estimate the performance of the proposed efficient sequential pattern matching [ESPM] algorithm for classified brain image system in terms of estimation of object position, efficiency and compared the results with an existing multiregion classifier method.
Mri brain image retrieval using multi support vector machine classifier
This document discusses content-based image retrieval (CBIR) for medical images. It proposes using multiple query images instead of a single query image to improve retrieval accuracy. The system works by preprocessing queries, extracting features like texture from the queries, optimizing the features, using classifiers like SVM to categorize images, and then using KNN to retrieve similar images from the database based on feature matching. It claims this approach improves on existing CBIR systems that rely on annotations and have difficulties bridging the semantic gap between low-level features and high-level meanings.
A Basic Knowledge of Image Morphing
The term "morphing" is used to describe the combination of generalized image warping with a crossdissolve
between image elements. The term is derived from "image metamorphosis". Morphing is an image
processing technique typically used as an animation tool for the metamorphosis from one image to another. The
idea is to specify a warp that distorts the first image into the second. Its inverse will distort the second image into
the first..The morph process consists of warping two images so that they have the same "shape", and then cross
dissolving the resulting images. Cross-dissolving is the major problem as how to warp an image. In this paper I
have concentrated on one of the methodology of image morphing named “Mesh Warping”.
Keywords: Morphing, Warping, Cross-dissolve, Metamorphosis.
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This document discusses motion estimation and compression techniques for video frames using true motion tracking. It begins with an abstract describing motion estimation as determining motion vectors between video frames to model the transformation from one frame to the next. It then discusses how motion estimation is used in video compression to exploit temporal redundancy by comparing frames and estimating displaced regions. The document provides details on algorithms like exhaustive search that perform motion estimation and compensation to reconstruct frames from motion vectors and residual differences.
Content-based image retrieval based on corel dataset using deep learning
A popular technique for retrieving images from huge and unlabeled image databases are content-based-image-retrieval (CBIR). However, the traditional information retrieval techniques do not satisfy users in terms of time consumption and accuracy. Additionally, the number of images accessible to users are growing due to web development and transmission networks. As the result, huge digital image creation occurs in many places. Therefore, quick access to these huge image databases and retrieving images like a query image from these huge image collections provides significant challenges and the need for an effective technique. Feature extraction and similarity measurement are important for the performance of a CBIR technique. This work proposes a simple but efficient deep-learning framework based on convolutional-neural networks (CNN) for the feature extraction phase in CBIR. The proposed CNN aims to reduce the semantic gap between low-level and high-level features. The similarity measurements are used to compute the distance between the query and database image features. When retrieving the first 10 pictures, an experiment on the Corel-1K dataset showed that the average precision was 0.88 with Euclidean distance, which was a big step up from the state-of-the-art approaches.
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image quality improvement of Low-resolution camera using Data fusion technique
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The document discusses using data fusion techniques to improve the quality of images from low-resolution cameras. It introduces data fusion and image fusion, explaining that the goal is to integrate multiple input images into a single higher-quality output image. The document then covers preprocessing input images using techniques like histograms and SVD analysis. It finds that fusing two low-quality images produces a higher-quality output image with improved frequency distribution and energy. In conclusion, data fusion is shown to create synergy and enhance image quality from low-cost cameras.Image processing
A process
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Matching Sketches with Digital Face Images using MCWLD and Image Moment Invar...
Face recognition is an important problem in many application domains. Matching sketches with
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automatically identifying a person from a still image. Law enforcement agencies are progressively using
composite sketches and forensic sketches for catching the criminals. This paper presents two algorithms that
efficiently retrieve the matched results. First method uses multiscale circular Weber’s local descriptor to encode
more discriminative local micro patterns from local regions. Second method uses image moments, it extracts
discriminative shape, orientation, and texture features from local regions of a face. The discriminating
information from both sketch and digital image is compared using appropriate distance measure. The
contributions of this research paper are: i) Comparison of multiscale circular Weber’s local descriptor with
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This document presents two algorithms for matching sketches to digital face images: 1) Multiscale Circular Weber's Local Descriptor (MCWLD) and 2) Image Moment Invariant. MCWLD encodes discriminative local micro patterns from local regions at multiple scales in a circular manner. Image Moment Invariant extracts shape, orientation, and texture features from local regions using image moments. Both extract distinguishing information from sketches and images, which are then compared using distance measures to find matches. The paper analyzes the performance of these algorithms on viewed, forensic, and composite sketch databases.
WEB IMAGE RETRIEVAL USING CLUSTERING APPROACHES
Image retrieval system is an active area to propose a new approach to retrieve images from the
large image database. In this concerned, we proposed an algorithm to represent images using
divisive based and partitioned based clustering approaches. The HSV color component and Haar wavelet transform is used to extract image features. These features are taken to segment an image to obtain objects. For segmenting an image, we used modified k-means clustering algorithm to group similar pixel together into K groups with cluster centers. To modify Kmeans, we proposed a divisive based clustering algorithm to determine the number of cluster and get back with number of cluster to k-means to obtain significant object groups. In addition, we also discussed the similarity distance measure using threshold value and object uniqueness to quantify the results.
Quality Assessment of Pixel-Level Image Fusion Using Fuzzy Logic
Image fusion is to reduce uncertainty and minimize redundancy in the output while maximizing relevant information from two or more images of a scene into a single composite image that is more informative and is more suitable for visual perception or processing tasks like medical imaging, remote sensing, concealed weapon detection, weather forecasting, biometrics etc. Image fusion combines registered images to produce a high quality fused image with spatial and spectral information. The fused image with more information will improve the performance of image analysis algorithms used in different applications. In this paper, we proposed a fuzzy logic method to fuse images from different sensors, in order to enhance the quality and compared proposed method with two other methods i.e. image fusion using wavelet transform and weighted average discrete wavelet transform based image fusion using genetic algorithm (here onwards abbreviated as GA) along with quality evaluation parameters image quality index (IQI), mutual information measure ( MIM), root mean square error (RMSE), peak signal to noise ratio (PSNR), fusion factor (FF), fusion symmetry (FS) and fusion index (FI) and entropy. The results obtained from proposed fuzzy based image fusion approach improves quality of fused image as compared to earlier reported methods, wavelet transform based image fusion and weighted average discrete wavelet transform based image fusion using genetic algorithm.
QUALITY ASSESSMENT OF PIXEL-LEVEL IMAGE FUSION USING FUZZY LOGIC
Image fusion is to reduce uncertainty and minimize redundancy in the output while maximizing relevant information from two or more images of a scene into a single composite image that is more informative and is more suitable for visual perception or processing tasks like medical imaging, remote sensing, concealed weapon detection, weather forecasting, biometrics etc. Image fusion combines registered images to
produce a high quality fused image with spatial and spectral information. The fused image with more information will improve the performance of image analysis algorithms used in different applications. In this paper, we proposed a fuzzy logic method to fuse images from different sensors, in order to enhance the
quality and compared proposed method with two other methods i.e. image fusion using wavelet transform and weighted average discrete wavelet transform based image fusion using genetic algorithm (here onwards abbreviated as GA) along with quality evaluation parameters image quality index (IQI), mutual
information measure ( MIM), root mean square error (RMSE), peak signal to noise ratio (PSNR), fusion factor (FF), fusion symmetry (FS) and fusion index (FI) and entropy. The results obtained from proposed fuzzy based image fusion approach improves quality of fused image as compared to earlier reported
methods, wavelet transform based image fusion and weighted average discrete wavelet transform based
image fusion using genetic algorithm.
APPLICATION OF IMAGE FUSION FOR ENHANCING THE QUALITY OF AN IMAGE
Advances in technology have brought about extensive research in the field of image fusion.
Image fusion is one of the most researched challenges of Face Recognition. Face Recognition
(FR) is the process by which the brain and mind understand, interpret and identify or verify
human faces.. Image fusion is the combination of two or more source images which vary in
resolution, instrument modality, or image capture technique into a single composite
representation. Thus, the source images are complementary in many ways, with no one input
image being an adequate data representation of the scene. Therefore, the goal of an image
fusion algorithm is to integrate the redundant and complementary information obtained from
the source images in order to form a new image which provides a better description of the scene
for human or machine perception. In this paper we have proposed a novel approach of pixel
level image fusion using PCA that will remove the image blurredness in two images and
reconstruct a new de-blurred fused image. The proposed approach is based on the calculation
of Eigen faces with Principal Component Analysis (PCA). Principal Component Analysis (PCA)
has been most widely used method for dimensionality reduction and feature extraction
Improving image resolution through the cra algorithm involved recycling proce...
Image processing concepts are widely used in medical fields. Digital images are prone to a
variety of types of noise. Noise is the result of errors in the image acquisition process for
reconstruction that result in pixel values that reflect the true intensities of the real scenes. A lot
of researchers are working on the field analysis and processing of multi-dimensional images.
Work previously hasn’t sufficient to stop them, so they continue performance work is due by the
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improvement about to image resolution. We proposed Concede Reconstruction Algorithm (CRA)
Involved Recycling Process to reduce the remained problem in improvement part of an image
processing. The CRA algorithms have better response from researcher to use them
IMPROVING IMAGE RESOLUTION THROUGH THE CRA ALGORITHM INVOLVED RECYCLING PROCE...
Image processing concepts are widely used in medical fields. Digital images are prone to a variety of types of noise. Noise is the result of errors in the image acquisition process for
reconstruction that result in pixel values that reflect the true intensities of the real scenes. A lot of researchers are working on the field analysis and processing of multi-dimensional images. Work previously hasn’t sufficient to stop them, so they continue performance work is due by the researcher. In this paper we contribute a novel research work for analysis and performance improvement about to image resolution. We proposed Concede Reconstruction Algorithm (CRA)
Involved Recycling Process to reduce the remained problem in improvement part of an image processing. The CRA algorithms have better response from researcher to use them.
Improving Graph Based Model for Content Based Image Retrieval
This document summarizes a research paper that proposes improvements to a graph-based model called Manifold Ranking (MR) for content-based image retrieval. Specifically, it introduces a novel scalable graph-based ranking model called Efficient Manifold Ranking (EMR) that addresses shortcomings of MR in scalable graph construction and efficient ranking computation. The proposed EMR model builds an anchor graph on the database instead of a traditional k-nearest neighbor graph, and designs a new form of adjacency matrix to speed up the ranking computation. Experimental results on large image databases demonstrate that EMR is effective for real-world image retrieval applications.
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Medical Image Processing � Detection of Cancer Brain
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Quality Assessment of Pixel-Level Image Fusion Using Fuzzy Logic
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Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Communications Mining Series - Zero to Hero - Session 1
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
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20240609 QFM020 Irresponsible AI Reading List May 2024
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In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
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Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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Microsoft - Power Platform_G.Aspiotis.pdf
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Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Securing your Kubernetes cluster_ a step-by-step guide to success !
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Join us to introduce Milvus Lite, a vector database that can run on notebooks and laptops, share the same API with Milvus, and integrate with every popular GenAI framework. This webinar is perfect for developers seeking easy-to-use, well-integrated vector databases for their GenAI apps.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
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- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
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Comparison of Articles on Content Based Image Retrieval
- 1. Comparison of Articles on Content Based Image Retrieval Elshalom Endrias
- 2. Outline Articles Introduction Definitions Article Summary Comparison Analysis Conclusion
- 3. Articles 1. Content –Based Image Retrieval Based on Electromagnetism-Like Mechanism” on Hindawi Publishing Corporation, Mathematical Problems in Engineering Volume 2013 available on http://dx.doi.org/10.1155/2013/782519 2. Content Based Image Retrieval using Exact Legendre Moments and Support Vector Machine on The International Journal of Multimedia and Its Application Volume 2, No.2, May 2010.
- 4. Introduction Attention in the potential of digital images has increased enormously over the last few years, fuelled at least in part by the rapid growth of imaging on the World-Wide Web. Many of collections are the product of digitizing exiting content of analog photographs, paints, diagrams and etc… Content-Based Image Retrieval (CBIR) is a new active research discipline focused on computational strategies to search for relevant images based on visual content analysis.
- 5. Definitions Content Based Image Retrieval (CBIR):- is a prominent area in image processing due to its diverse applications in internet, multimedia, medical image archives, and crime prevention. Image: - Images have rich content, and each image is described by its own features. Image Moment: - is certain particular weighted average (moment) of the image pixels’ intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. (Wikipedia)
- 6. Articles Summary CBIR Based on Electromagnetism-Like Mechanism Is based on based on electromagnetism optimization technique that follows the collective attraction-repulsion mechanism by considering each image as electrical charge CBIR Based on Exact Legendre Moments and Support Vector Machine Id based on shape using invariant image moments, viz, Moment Invariants (MI) and Zernike Moments (ZM) are available in the article.
- 8. Image Representation Electromagnetism-Like Mechanisms originally came from the electromagnetism theory in physics, which simulates the electromagnetism theory by considering each particle to be an electrical charge Exact Legendre Moments and Support Vector Machine represent images using image moments like (Moment Invariants, Zernike Moments, Exact Legendre Moments and Support Vector Machine)
- 9. Similarity Measurement Retrieved images are ranked by their Euclidean distance in Electromagnetism-Like Mechanisms Similarities are viewed on the image database as two sets of vectors in an “n” dimensional space and constructs a separating hyper plane that maximizes the margin between the images relevant to query and images not relevant to the query in Exact Legendre and Support Vector Machine
- 10. Learning Mechanism Learning is not provided in Electromagnetism-Like Mechanism Learning is provided in Exact Legendre Moments and Support Vector Machine and mostly training of the system is very important in Exact Legendre and Support Vector Machine
- 11. Experiments Electromagnetism-Like Mechanisms, experiments were carried out on a subset of images from the Corel Photo Gallery. This subset contains about 20,000 images of very diverse subject matter. Exact Legendre Moments and Support Vector Machine Corel shape database, COIL-20, 20 classes of images with each class consisting of 72 different orientations resulting in a total of 1440 images. And a result of
- 12. Results Electromagnetism-Like Mechanisms’ algorithm is able to advance the overall average precision to 83.57% and 64.10% using noisy or blurred query image. Exact Legendre Moments and Support Vector Machine algorithm is capable of 62.75% average precision.
- 13. Analysis Extraction of visual features, color, texture, and shape is an important component of CBIR plus speed and accuracy Exact Legendre Moments and Support Vector Machine presents image as geometric object with approximation. Electromagnetism-Like Mechanisms represent as electromagnet charge. Electromagnetism-Like Mechanisms has high precession than Exact Legendre Moments and Support Vector Machine
- 14. Conclusion Moment invariants have been widely applied to image pattern recognition due to its invariant features on image translation, scaling and rotation. Electromagnetism has both been successfully applied to constraint project scheduling problems, vehicle routing, array pattern optimization, image processing, neural network training and control system.