Performance of Efficient Closed-Form Solution to Comprehensive Frontier Exposureiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The development of multimedia system technology in Content based Image Retrieval (CBIR) System is
one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature
vectors of the query image are compared with feature vectors of the database images to get matching images.It is
much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an
intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR
technique that suits for a selected sort of images. The Extraction of an image includes feature description and
feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level Co-
Occurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that
extract the matching image based on the similarity of Color, Texture and shape within the database. For
performance analysis, the image retrieval timing results of the projected technique is calculated and compared
with every of the individual feature.
Hashing is popular technique of image authentication to identify malicious attacks and it also allows appearance changes in an image in controlled way. Image hashing is quality summarization of images. Quality summarization implies extraction and representation of powerful low level features in compact form. Proposed adaptive CSLBP compressed hashing method uses modified CSLBP (Center Symmetric Local Binary Pattern) as a basic method for texture extraction and color weight factor derived from L*a*b* color space. Image hash is generated from image texture. Color weight factors are used adaptively in average and difference forms to enhance discrimination capability of hash. For smooth region, averaging of colours used while for non-smooth region, color differencing is used. Adaptive CSLBP histogram is a compressed form of CSLBP and its quality is improved by adaptive color weight factor. Experimental results are demonstrated with two benchmarks, normalized hamming distance and ROC characteristics. Proposed method successfully differentiate between content change and content persevering modifications for color images.
Abstract Image Segmentation plays a vital role in image processing. The research in this area is still relevant due to its wide applications. Image segmentation is a process of assigning a label to every pixel in an image such that pixels with same label share certain visual characteristics. Sometimes it becomes necessary to calculate the total number of colors from the given RGB image to quantize the image, to detect cancer and brain tumour. The goal of this paper is to provide the best algorithm for image segmentation. Keywords: Image segmentation, RGB
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Performance of Efficient Closed-Form Solution to Comprehensive Frontier Exposureiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The development of multimedia system technology in Content based Image Retrieval (CBIR) System is
one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature
vectors of the query image are compared with feature vectors of the database images to get matching images.It is
much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an
intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR
technique that suits for a selected sort of images. The Extraction of an image includes feature description and
feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level Co-
Occurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that
extract the matching image based on the similarity of Color, Texture and shape within the database. For
performance analysis, the image retrieval timing results of the projected technique is calculated and compared
with every of the individual feature.
Hashing is popular technique of image authentication to identify malicious attacks and it also allows appearance changes in an image in controlled way. Image hashing is quality summarization of images. Quality summarization implies extraction and representation of powerful low level features in compact form. Proposed adaptive CSLBP compressed hashing method uses modified CSLBP (Center Symmetric Local Binary Pattern) as a basic method for texture extraction and color weight factor derived from L*a*b* color space. Image hash is generated from image texture. Color weight factors are used adaptively in average and difference forms to enhance discrimination capability of hash. For smooth region, averaging of colours used while for non-smooth region, color differencing is used. Adaptive CSLBP histogram is a compressed form of CSLBP and its quality is improved by adaptive color weight factor. Experimental results are demonstrated with two benchmarks, normalized hamming distance and ROC characteristics. Proposed method successfully differentiate between content change and content persevering modifications for color images.
Abstract Image Segmentation plays a vital role in image processing. The research in this area is still relevant due to its wide applications. Image segmentation is a process of assigning a label to every pixel in an image such that pixels with same label share certain visual characteristics. Sometimes it becomes necessary to calculate the total number of colors from the given RGB image to quantize the image, to detect cancer and brain tumour. The goal of this paper is to provide the best algorithm for image segmentation. Keywords: Image segmentation, RGB
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Multi Resolution features of Content Based Image RetrievalIDES Editor
Many content based retrieval systems have been
proposed to manage and retrieve images on the basis of their
content. In this paper we proposed Color Histogram, Discrete
Wavelet Transform and Complex Wavelet Transform
techniques for efficient image retrieval from huge database.
Color Histogram technique is based on exact matching of
histogram of query image and database. Discrete Wavelet
transform technique retrieves images based on computation
of wavelet coefficients of subbands. Complex Wavelet
Transform technique includes computation of real and
imaginary part to extract the details from texture. The
proposed method is tested on COREL1000 database and
retrieval results have demonstrated a significant improvement
in precision and recall.
Text-Image Separation in Document Images using Boundary/Perimeter DetectionIDES Editor
Document analysis plays an important role in office
automation, especially in intelligent signal processing. The
proposed system consists of two modules: block segmentation
and block identification. In this approach, first a document is
segmented into several non-overlapping blocks by utilizing a
novel recursive segmentation technique, and then extracts
the features embedded in each segmented block are extracted.
Two kinds of features, connected components and image
boundary/perimeter features are extracted. Document with
text inside image pose limitations in earlier reported literature.
This is taken care of by applying additional pass of the Run
Length Smearing on the extracted image that contains text.
Proposed scheme is independent of type and language of the
document.
EFFICIENT IMAGE RETRIEVAL USING REGION BASED IMAGE RETRIEVALsipij
Early image retrieval techniques were based on textual annotation of images. Manual annotation of images
is a burdensome and expensive work for a huge image database. It is often introspective, context-sensitive
and crude. Content based image retrieval, is implemented using the optical constituents of an image such
as shape, colour, spatial layout, and texture to exhibit and index the image. The Region Based Image
Retrieval (RBIR) system uses the Discrete Wavelet Transform (DWT) and a k-means clustering algorithm
to segment an image into regions. Each region of the image is represented by a set of optical
characteristics and the likeness between regions and is measured using a particular metric function on
such characteristics
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.
Marker Controlled Segmentation Technique for Medical applicationRushin Shah
Medical image segmentation is a very important field for the medical science. In medical images, edge detection is an important work for object recognition of the human organs such as brain, heart or kidney etc. and it is an essential pre-processing step in medical image segmentation.
Medical images such as CT, MRI or X-Ray visualizes the various information’s of internal organs which is very important for doctors diagnoses as well as medical teaching, learning and research.
It is a tough job to locate the internal organs if images contains noise or rough structure of human body organs.
FORGERY (COPY-MOVE) DETECTION IN DIGITAL IMAGES USING BLOCK METHODeditorijcres
AKHILESH KUMAR YADAV, DEENBANDHU SINGH, VIVEK KUMAR
Department of Computer Science and Engineering
Babu Banarasi Das University, Lucknow
akhi2232232@gmail.com, deenbandhusingh85@gmail.com, vivek.kumar0091@gmail.com
ABSTRACT- Digital images can be easily modified using powerful image editing software. Determining whether a manipulation is innocent of sharpening from those which are malicious, such as removing or adding parts to an image is the topic of this paper. In this paper we focus on detection of a special type of forgery-the Copy-Move forgery, in this part of the original image is copied moved to desired location in the same image and pasted. The proposed method compress images using DWT (discrete wavelet transform) and divided into blocks and choose blocks than perform feature vector calculation and lexicographical sorting and duplicated blocks are identified after sorting. This method is good at some manipulation/attack likes scaling, rotation, Gaussian noise, smoothing, JPEG compression etc.
INDEX TERMS- Copy-Move forgery, Wavelet Transform, Lexicographical Sorting, Region Duplication Detection.
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.
A Robust Object Recognition using LBP, LTP and RLBPEditor IJMTER
In this paper two set of edge-texture features is proposed such as Discriminative Robust
Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for
object recognition. The proposed DLBP and DRLTP are derived from the drawback of the Local
Binary Pattern (LBP), Local Ternary Pattern (LTP) and Robust LBP (RLBP).The LBP code and the
RLBP code are mapped in the same block .The proposed feature solves the problem of
discrimination between a bright object against dark background and vice-versa. The proposed feature
retains contrast information for representation of object contours the LBP, LTP and RLBP discards.
By this proposed features the objects in the image can be further analyzed for the exact location of
the object in the given image.
Multi Resolution features of Content Based Image RetrievalIDES Editor
Many content based retrieval systems have been
proposed to manage and retrieve images on the basis of their
content. In this paper we proposed Color Histogram, Discrete
Wavelet Transform and Complex Wavelet Transform
techniques for efficient image retrieval from huge database.
Color Histogram technique is based on exact matching of
histogram of query image and database. Discrete Wavelet
transform technique retrieves images based on computation
of wavelet coefficients of subbands. Complex Wavelet
Transform technique includes computation of real and
imaginary part to extract the details from texture. The
proposed method is tested on COREL1000 database and
retrieval results have demonstrated a significant improvement
in precision and recall.
Text-Image Separation in Document Images using Boundary/Perimeter DetectionIDES Editor
Document analysis plays an important role in office
automation, especially in intelligent signal processing. The
proposed system consists of two modules: block segmentation
and block identification. In this approach, first a document is
segmented into several non-overlapping blocks by utilizing a
novel recursive segmentation technique, and then extracts
the features embedded in each segmented block are extracted.
Two kinds of features, connected components and image
boundary/perimeter features are extracted. Document with
text inside image pose limitations in earlier reported literature.
This is taken care of by applying additional pass of the Run
Length Smearing on the extracted image that contains text.
Proposed scheme is independent of type and language of the
document.
EFFICIENT IMAGE RETRIEVAL USING REGION BASED IMAGE RETRIEVALsipij
Early image retrieval techniques were based on textual annotation of images. Manual annotation of images
is a burdensome and expensive work for a huge image database. It is often introspective, context-sensitive
and crude. Content based image retrieval, is implemented using the optical constituents of an image such
as shape, colour, spatial layout, and texture to exhibit and index the image. The Region Based Image
Retrieval (RBIR) system uses the Discrete Wavelet Transform (DWT) and a k-means clustering algorithm
to segment an image into regions. Each region of the image is represented by a set of optical
characteristics and the likeness between regions and is measured using a particular metric function on
such characteristics
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.
Marker Controlled Segmentation Technique for Medical applicationRushin Shah
Medical image segmentation is a very important field for the medical science. In medical images, edge detection is an important work for object recognition of the human organs such as brain, heart or kidney etc. and it is an essential pre-processing step in medical image segmentation.
Medical images such as CT, MRI or X-Ray visualizes the various information’s of internal organs which is very important for doctors diagnoses as well as medical teaching, learning and research.
It is a tough job to locate the internal organs if images contains noise or rough structure of human body organs.
FORGERY (COPY-MOVE) DETECTION IN DIGITAL IMAGES USING BLOCK METHODeditorijcres
AKHILESH KUMAR YADAV, DEENBANDHU SINGH, VIVEK KUMAR
Department of Computer Science and Engineering
Babu Banarasi Das University, Lucknow
akhi2232232@gmail.com, deenbandhusingh85@gmail.com, vivek.kumar0091@gmail.com
ABSTRACT- Digital images can be easily modified using powerful image editing software. Determining whether a manipulation is innocent of sharpening from those which are malicious, such as removing or adding parts to an image is the topic of this paper. In this paper we focus on detection of a special type of forgery-the Copy-Move forgery, in this part of the original image is copied moved to desired location in the same image and pasted. The proposed method compress images using DWT (discrete wavelet transform) and divided into blocks and choose blocks than perform feature vector calculation and lexicographical sorting and duplicated blocks are identified after sorting. This method is good at some manipulation/attack likes scaling, rotation, Gaussian noise, smoothing, JPEG compression etc.
INDEX TERMS- Copy-Move forgery, Wavelet Transform, Lexicographical Sorting, Region Duplication Detection.
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.
A Robust Object Recognition using LBP, LTP and RLBPEditor IJMTER
In this paper two set of edge-texture features is proposed such as Discriminative Robust
Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for
object recognition. The proposed DLBP and DRLTP are derived from the drawback of the Local
Binary Pattern (LBP), Local Ternary Pattern (LTP) and Robust LBP (RLBP).The LBP code and the
RLBP code are mapped in the same block .The proposed feature solves the problem of
discrimination between a bright object against dark background and vice-versa. The proposed feature
retains contrast information for representation of object contours the LBP, LTP and RLBP discards.
By this proposed features the objects in the image can be further analyzed for the exact location of
the object in the given image.
Interfacing of Java 3D objects for Virtual Physics Lab (VPLab) Setup for enco...IOSR Journals
During this paper we target the combination of web accessible physics experiments (VPLabs) combined with the Sun’s toolkit for making cooperative 3D virtual worlds. Among such a cooperative setting these tools give the chance for academics and students to figure along as avatars as they control actual instrumentation, visualize natural phenomenon generated by the experiment, and discuss the results. Especially we'll define the steps of integration, future goals, yet because the price of a collaboration area in Wonderland's virtual world.
A Novel Feature Extraction Scheme for Medical X-Ray ImagesIJERA Editor
X-ray images are gray scale images with almost the same textural characteristic. Conventional texture or color
features cannot be used for appropriate categorization in medical x-ray image archives. This paper presents a
novel combination of methods like GLCM, LBP and HOG for extracting distinctive invariant features from Xray
images belonging to IRMA (Image Retrieval in Medical applications) database that can be used to perform
reliable matching between different views of an object or scene. GLCM represents the distributions of the
intensities and the information about relative positions of neighboring pixels of an image. The LBP features are
invariant to image scale and rotation, change in 3D viewpoint, addition of noise, and change in illumination A
HOG feature vector represents local shape of an object, having edge information at plural cells. These features
have been exploited in different algorithms for automatic classification of medical X-ray images. Excellent
experimental results obtained in true problems of rotation invariance, particular rotation angle, demonstrate that
good discrimination can be achieved with the occurrence statistics of simple rotation invariant local binary
patterns.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
Density Driven Image Coding for Tumor Detection in mri ImageIOSRjournaljce
The significant of multi spectral band resolution is explored towards selection of feature coefficients based on its energy density. Toward the feature representiaon in transformed domain, multi wavelet transformations were used for finer spectral representation. However, due to a large feature count these features are not optimal under low resource computing system. In the recognition units, running with low resources a new coding approach of feature selection, considering the band spectral density is developed. The effective selection of feature element, based on its spectral density achieve two objective of pattern recognition, the feature coefficient representiaon is minimized, hence leading to lower resource requirement, and dominant feature representation, resulting in higher retrieval performance.
Copy Move Forgery Detection Using GLCM Based Statistical Features ijcisjournal
The features Gray Level Co-occurrence Matrix (GLCM) are mostly explored in Face Recognition and
CBIR. GLCM technique is explored here for Copy-Move Forgery Detection. GLCMs are extracted from all
the images in the database and statistics such as contrast, correlation, homogeneity and energy are
derived. These statistics form the feature vector. Support Vector Machine (SVM) is trained on all these
features and the authenticity of the image is decided by SVM classifier. The proposed work is evaluated on
CoMoFoD database, on a whole 1200 forged and processed images are tested. The performance analysis
of the present work is evaluated with the recent methods.
Orientation Spectral Resolution Coding for Pattern RecognitionIOSRjournaljce
In the approach of pattern recognition, feature descriptions are of greater importance. Features are represented in spatial domain and transformed domain. Wherein, spatial domain features are of lower representation, transformed domains are finer and more informative. In the transformed domain representation, features are represented using spectral coding using advanced transformation technique such as wavelet transformation. However, the feature extraction approach considers the band coefficients; the orientation variation is not considered. In this paper towards inherent orientation variation among each spectral band is derived, and the approach of orientation filtration is made for effective feature representation. The obtained result illustrates an improvement in the recognition accuracy, in comparison to conventional retrieval system.
Empirical Coding for Curvature Based Linear Representation in Image Retrieval...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
An Unsupervised Change Detection in Satellite IMAGES Using MRFFCM ClusteringEditor IJCATR
This paper presents a new approach for change detection in synthetic aperture radar images by incorporating Markov random field (MRF) within the framework of FCM. The objective is to partition the difference image which is generated from multitemporal satellite images into changed and unchanged regions. The difference image is generated from log ratio and mean ratio images by image fusion technique. The quality of difference image depends on image fusion technique. In the present work; we have proposed an image fusion method based on stationary wavelet transform. To process the difference image is to discriminate changed regions from unchanged regions using fuzzy clustering algorithms. The analysis of the DI is done using Markov random field (MRF) approach that exploits the interpixel class dependency in the spatial domain to improve the accuracy of the final change-detection areas. The experimental results on real synthetic aperture radar images demonstrate that change detection results obtained by the MRFFCM exhibits less error than previous approaches. The goodness of the proposed fusion algorithm by well-known image fusion measures and the percentage correct classifications are calculated and verified.
Multiple Ant Colony Optimizations for Stereo MatchingCSCJournals
The stereo matching problem, which obtains the correspondence between right and left images, can be cast as a search problem. The matching of all candidates in the same line forms a 2D optimization task and the two dimensional (2D) optimization is a NP-hard problem. There are two characteristics in stereo matching. Firstly, the local optimization process along each scan-line can be done concurrently; secondly, there are some relationship among adjacent scan-lines can be explored to promote the matching correctness. Although there are many methods, such as GCPs, GGCPs are proposed, but these so called GCPs maybe not be ground. The relationship among adjacent scan-lines is posteriori, that is to say the relationship can only be discovered after every optimization is finished. The Multiple Ant Colony Optimization(MACO) is efficient to solve large scale problem. It is a proper way to settle down the stereo matching task with constructed MACO, in which the master layer values the sub-solutions and propagate the reliability after every local optimization is finished. Besides, whether the ordering and uniqueness constraints should be considered during the optimization is discussed, and the proposed algorithm is proved to guarantee its convergence to find the optimal matched pairs.
Comparison of various Image Registration Techniques with the Proposed Hybrid ...idescitation
Image Registration is termed as the method to
transform different forms of image data into one coordinate
system. Registration is a important part in image processing
which is used for matching the pictures which are obtained at
different time intervals or from various sensors. A broad range
of registration techniques have been developed for the various
types of image data. These techniques are independently
studied for many applications resulting in the large body of
result. Vision is the most advanced of human sensors, so
naturally images play one of the most important roles in
human perception. Image registration is one of the branches
encompassed by the diverse field of digital image processing.
Due to its importance in many application areas as well as
since its nature is complicated; image registration is now the
topic of much recent research. Registration algorithms tend
to compute transformations to set correspondence betweenthe two images. In this paper the survey is done on various
image registration techniques. Also the different techniques
are compared with the proposed system of the projec
Super-resolution (SR) is the process of obtaining a high resolution (HR) image or
a sequence of HR images from a set of low resolution (LR) observations. The block
matching algorithms used for motion estimation to obtain motion vectors between the
frames in Super-resolution. The implementation and comparison of two different types of
block matching algorithms viz. Exhaustive Search (ES) and Spiral Search (SS) are
discussed. Advantages of each algorithm are given in terms of motion estimation
computational complexity and Peak Signal to Noise Ratio (PSNR). The Spiral Search
algorithm achieves PSNR close to that of Exhaustive Search at less computation time than
that of Exhaustive Search. The algorithms that are evaluated in this paper are widely used
in video super-resolution and also have been used in implementing various video standards
like H.263, MPEG4, H.264.
Content Based Image Retrieval Approach Based on Top-Hat Transform And Modifie...cscpconf
In this paper a robust approach is proposed for content based image retrieval (CBIR) using texture analysis techniques. The proposed approach includes three main steps. In the first one, shape detection is done based on Top-Hat transform to detect and crop object part of the image. Second step is included a texture feature representation algorithm using color local binary patterns (CLBP) and local variance features. Finally, to retrieve mostly closing matching images to the query, log likelihood ratio is used. The performance of the proposed approach is evaluated using Corel and Simplicity image sets and it compared by some of other well-known approaches in terms of precision and recall which shows the superiority of the proposed approach. Low noise sensitivity, rotation invariant, shift invariant, gray scale invariant and low computational complexity are some of other advantages.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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H017416670
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 4, Ver. I (July – Aug. 2015), PP 66-70
www.iosrjournals.org
DOI: 10.9790/0661-17416670 www.iosrjournals.org 66 | Page
Copy-Move Image Forgery Detection Based on Center-Symmetric
Local Binary Pattern
1
Vandana Sangwan, 2
Madan Lal
1, 2
Department of Computer Engineering Punjabi University Patiala-147002, (India)
Abstract: This paper presents a method to detect copy-move image forgery using CS-LBP (centre symmetric
local binary pattern), an extension of basic local binary pattern. In the proposed method, firstly gray level
conversion is performed on the given image. Later, the image will be decomposed into fixed sized non-
overlapping blocks. Feature extraction can be done using CS- LBP, as this technique is invariant to illumination
and rotation. Then distance between the extracted feature vectors is calculated and are sorted
lexicographically, and retained only those pairs of blocks that have minimal distances between them. Those
minimal distances compared with predefined threshold value serve as the purpose of the copied regions. In the
end, post-processing is done using morphological operation and mask is generated for the region detected as
forged region.
Keywords: Copy-move forgery detection, CS-LBP, feature extraction, Image Tampering.
I. Introduction
In today’s technological era, digital images are the basic form of conveying information. But the
authenticity of these images is a big question for the society. As digital images are used in every field, for
example medical imaging, satellite imaging, forensic labs, and journalism for easy visualization, so preserving
their originality is a major issue. The popularity of digital images leads to the research in this area. With the help
of easy availability of photo editing software, an image can be tampered easily. This image tampering is
basically image forgery which is carried out to present false information or modify the real content of the image.
There are three main classes of image forgery, namely image retouching, copy-move forgery and image
splicing. Image re-touching involves rotation, scaling, contrast enhancement and resizing. In copy-move
forgery, an object or portion of the image is copied and pasted on to the other location in the same image so as
to hide some information or alter the original content of the image. Here, the basic characteristics of the image
remain same such as color, texture. Thirdly, the image splicing is a forgery that is a combination of two or more
than two images and results into a new image. Image splicing sources are heterogeneous as contents can be
picked from anywhere. The approaches to detect the digital image forgery are classified into two categories,
active and passive. In active forgery, some form of watermarking information is present in the image. In passive
or blind forgery, there is no such information is hidden in the image. Copy move forgery is an example of
passive (blind) forgery which will be detected using center-symmetric local binary pattern scheme.
In this paper, a passive method to detect copy move forgery in digital images is proposed. Firstly, we
divide the image into overlapping blocks after converting it into gray scale. Then using CS-LBP, feature vectors
are to be extracted. This technique overcomes with the drawbacks of basic local binary pattern, such as variant
to illumination and it is not too robust on flat image areas i.e. variance of intensity values within the uniform
region is very low. CS-LBP preserves better gradient information while preserving distinctiveness, reduce
dimensions also. Then lexicographical sorting is done on the feature vectors so as to bring the similar pairs of
vectors together for easy recognition. Finally the distance between those vectors is calculated and compared
with a threshold value to detect the duplicated region. The rest of the paper is as follows. In section 2, some
previously related work has being discussed, section 3 introduces CS-LBP operation. In section 4, proposed
algorithm is presented, followed with the results and conclusion in section 6.
II. Related Works
In this section, we have reviewed the passive methods for detection of copy-move forgery. Among the
initial attempts J. Fridrich, D. Soukal and J. Lukas [1] proposed methods to detect copy-move forgery. Discrete
cosine transform (DCT) of the image blocks was used and their lexicographical sorting is taken to avoid the
computational burden. Once sorted the adjacent identical pair of blocks are considered to be copy-moved
blocks. Block matching algorithm was used for balance between performance and complexity. This method
suffers from the drawback that it cannot detect small duplicate regions. Mohammad Farukh Hashmi, Vijay
Anand, Avinas G Keskar [2] proposed method using un-decimated wavelet transform along with SIFT operator
to extract more number of key-points that are matched to detect the copied blocks efficiently. This method gives
better results than DWT.
2. Copy-Move Image Forgery Detection Based on Center-Symmetric…
DOI: 10.9790/0661-17416670 www.iosrjournals.org 67 | Page
Mohammad Hussain et al, [3] showed a method based upon multi-resolution Weber law descriptors
(WLD. The suggested multi-resolution WLD extracts the features from chrominance components. An SVM is
used for classification and the experimental results showed that the accuracy rate can reach up to 91%.
Ning Zheng, Yixing Wang and Ming Xu [4] used a block based method to describe the components
extracted using LBP operator which is rotationally invariant. This method gives better results to post-processing
and rotation effects. Later on, technique presented by B.L. Shiva kumar et al, [5] using SURF and KD-tree for
data matching step results in minimal false matches if images of high resolution being taken.
Reza Davarzani, Khashayar Yaghmie et al, [6] presented a method based on multi-resolution local
binary pattern. This method is robust to geometric changes and illumination variations of the copied portions.
They proposed this method against after various variations such as rotation, blurring, noise addition, and JPEG
compression.
Motasem Alsawadi et al, [7] introduced a method based on basic local binary pattern with
neighborhood clustering to refine the features. This method shows the reduction in matching false regions.
Various techniques have been proposed and research is still going on. We tried to put our novel method
using variation of LBP, which is CS-LBP, so as to overcome the problems faced with local binary pattern.
III. Proposed Algorithm
The proposed step-wise methodology is as shown in fig.1.
Fig. 1 Block diagram of proposed method
3. Copy-Move Image Forgery Detection Based on Center-Symmetric…
DOI: 10.9790/0661-17416670 www.iosrjournals.org 68 | Page
Step-1: Gray Scale Conversion
Firstly, the given input image is converted to gray scale according to the following equation.
Y = 0.299R + 0.587G + 0.114B (1)
Where, Y is luminance component. Also a gray scale image is simple to work with.
Step-2: Division of image into overlapping blocks
The next step is to decompose the image (gray scale image) into fixed sized overlapping blocks. The block size
is chosen to be the minimal size of image tampering portion. For an image of size M*N, the total number of
blocks formed are given as per the following equation.
TB = (M-B+1)(N-B+1) (2)
Step-3: Feature extraction using CS-LBP
In this phase, features are extracted from the blocks using center-symmetric local binary pattern. CS-LBP is a
variant of local binary pattern, which is free from illumination variances and rotation effects. CS-LBP also
yields less number of feature vectors as compared to LBP so to make this technique less time consuming, as
shown in fig.2. For an image of M*N dimensions, local binary pattern produces 256 different binary patterns,
whereas for CS-LBP this number is only 16. Furthermore, robustness on flat image regions is obtained by
thresholding the gray-level differences with a small value T.
Fig. 2 Extraction of CS-LBP feature vectors The value of the threshold T is 1% of the pixel value
CSLBPR,N,T x, y = s ni − ni+(N 2)
N 2 −1
i=0
2i
,
Where s x =
1 x > T
0 otherwise
(3)
Range in our experiments. Since the region data lies between 0 and 1, T is set to 0.01. The radius is set to 2 and the
size of the neighborhood is 8. It should be noted that the gain of CS-LBP over LBP is not only due to the
dimensionality reduction, but also to the fact that the CS-LBP captures better the gradient information than the
basic LBP.
A texture descriptor used in passive forgery detection of copy move forgery should be rotationally
invariant, so that if the copied region is rotated before pasting into the same image, it can still be detected.
Rotational invariant CSLBP can be express by the Eq. (2):
CSLBPN,R
ri
= min{ROR(CSLBPN, R, i ) | i==0,1…N} Eq. (2)
Where, function ROR (z, i) represents circular bitwise rotation of sequence z by i steps.
Step-4: Calculation of distance & Lexicographical sorting
dij = xi − xj ^2 + yi − yj ^2 where (xi, yi) is the top-left corner’s coordinate of the i-th block.
This type of sorting is applied on the rows of the matrix. In the organized list, homogeneous rows are proximate
to each other.
Step-5: Post-Processing
Morphologic operations are applied to fill the holes in the marked regions and remove the isolated points, then
output the final result.
IV. Results
The experiments were carried on Dell laptop having Core2 Duo processor with 2GB RAM using
MATLAB 2012a.The database on which we conducted our test contains a total of 220 images, in which 110
images are original images and remaining 110 images are forged images.
4. Copy-Move Image Forgery Detection Based on Center-Symmetric…
DOI: 10.9790/0661-17416670 www.iosrjournals.org 69 | Page
Also, true positive rate and false positive rate is being calculated to analyze the performance of the
proposed system quantitatively. TPR is the percentage of correctly identified forged images while FPR is the
percentage of original images falsely identified as forged.
Fig. 3: (a) Original image, (b) CS-LBP extracted feature representation,(c) forged image,(d) shows the generation of mask of
forged area in the image.
Fig. 4: (a) Original image, (b) Feature extraction using CS-LBP, (c) forged image, (d) shows mask generation of
the forged portion in image.
5. Copy-Move Image Forgery Detection Based on Center-Symmetric…
DOI: 10.9790/0661-17416670 www.iosrjournals.org 70 | Page
V. Conclusion
A novel CS-LBP interest region descriptor which combines the strengths of the well known SIFT
descriptor and the LBP texture operator was proposed. SIFT operator reduces the length of feature vector, so
analyzing feature vectors will take less time. This method gives better result than using LBP alone, TPR ratio
value is more, while the false positives are decreased using morphological operation. Overall accuracy of the
proposed system outperforms simple LBP technique. There can be a scope for future work on this technique
such as verifying this technique on other image formats and also different post-processing effects.
References
[1]. J. Fridrich, B. D. Soukal, and A. J. Lukas, “Detection of copy move forgery in digital images,” in Proceedings of the Digital
Forensic Research Workshop, Cleveland, Ohio, USA,August 2003.
[2]. Mohammad Farukh Hashmia et al, “Copy-move Image Forgery Detection Using an Efficient and Robust Method Combining Un-
decimated Wavelet Transform and Scale Invariant Feature Transform” 2014 AASRI Conference on Circuit and Signal Processing
(CSP 2014).
[3]. G. Muhammad, M. Hussain, G. Bebis, “Passive copy move image forgery detection using undecimated dyadic wavelet transform,”
Digital Investigation, vol. 9 (1), pp. 49-57, 2012.
[4]. Ning Zheng, Yixing Wang and Ming Xu, “A LBP Based Method for Detecting Copy-Move Forgery with Rotation,” Springer
Science, pp. 261-267,2013.
[5]. B. L. Shivakumar and Lt. Dr. Santhosh. "Detecting copy-move forgery in Digital images: A survey and analysis of current
methods," Global Journal of Computer Science and Technology, vol. 10, no. 7, 2010.
[6]. R. Davarzani, K. Yaghmaie, S. Mozaffari, and M. Tapak, “Copymove forgery detection using multiresolution local binary
patterns”, Forensics Science International, vol. 231, pp. 61-72, 2013.
[7]. Motasem Alsawadi et al, “Copy-Move Image Forgery Detection Using Local Binary Pattern and Neighborhood Clustering,” IEEE,
pp. 249-254, 2013.