Content based image retrieval using features extracted from halftoning-based block truncation coding

•Download as DOCX, PDF•

0 likes•197 views

IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar

Engineering

Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Title: Effective Image Retrieval System Using
Dot-Diffused Block Truncation Coding
Features
Abstract—This paper presents a new approach to derive the image feature
descriptor from the dot-diffused block truncation coding (DDBTC) compressed
data stream. The image feature descriptor is simply constructed from two DDBTC
representative color quantizers and its corresponding bitmap image. The color
histogram feature (CHF) derived from two color quantizers represents the color
distribution and image contrast, while the bit pattern feature (BPF) constructed
from the bitmap image characterizes the image edges and textural information. The
similarity between two images can be easily measured from their CHF and BPF
values using a specific distance metric computation. Experimental results
demonstrate the superiority of the proposed feature descriptor compared to the
former existing schemes in image retrieval task under natural and textural images.
The DDBTC method compresses an image efficiently, and at the same time, its
corresponding compressed data stream can provide an effective feature descriptor
for performing image retrieval and classification. Consequently, the proposed
scheme can be considered as an effective candidate for real-time image retrieval
applications.

Software & Hardware requirement:
1. Hardware requirement:
1. PC
2. RAM minimum 2GB
3. HDD minimum 100GB
2. Software requirement:
1. MATLAB 7.0
2. Signal processing toolbox
3. Image processing toolbox
4. Mathematical toolbox
PROJECT FLOW:
First Review:
Literature Survey
Paper Explanation
Design of Project
Project Enhancement explanation
Second Review:
Implementing 40% of Base Paper
Third Review
Implementing Remaining 60% of Base Paper with Future Enhancement
(Modification)
For More Details please contact
Logic Mind Technologies
Vijayangar (Near Maruthi Medicals), Bangalore-40
Ph: 8123668124 // 8123668066
Mail: logicmindtech@gmail.com

What's hot

Literature Review on Content Based Image Retrieval

Upekha Vandebona

Content-Based Image Retrieval (CBIR) systems have been used for the searching of relevant images in various research areas. In CBIR systems features such as shape, texture and color are used. The extraction of features is the main step on which the retrieval results depend. Color features in CBIR are used as in the color histogram, color moments, conventional color correlogram and color histogram. Color space selection is used to represent the information of color of the pixels of the query image. The shape is the basic characteristic of segmented regions of an image. Different methods are introduced for better retrieval using different shape representation techniques; earlier the global shape representations were used but with time moved towards local shape representations. The local shape is more related to the expressing of result instead of the method. Local shape features may be derived from the texture properties and the color derivatives. Texture features have been used for images of documents, segmentation-based recognition,and satellite images. Texture features are used in different CBIR systems along with color, shape, geometrical structure and sift features.

Content-Based Image Retrieval Features: A Survey

Eswar Publications

CBIR

Durga Kinge

Content Based Image and Video Retrieval Algorithm

Akshit Bum

The paper presents an extension of content based image retrieval (CBIR) techniques based on multilevel Block Truncation Coding (BTC) using nine sundry color spaces. Block truncation coding based features is one of the CBIR methods proposed using color features of image. The approach basically considers red, green and blue planes of an image to compute feature vector. This BTC based CBIR can be extended as multileveled BTC for performance improvement in image retrieval. The paper extends the multileveled BTC using RGB color space to other nine color spaces. The CBIR techniques like BTC Level-1, BTC Level-2, BTC Level-3 and BTC Level-4 are applied using various color spaces to analyze and compare their performances. The CBIR techniques are tested on generic image database of 1000 images spread across 11 categories. For each CBIR technique, 55 queries (5 per category) are fired on extended Wang generic image database to compute average precision and recall for all queries. The results have shown the performance improvement (ie., higher precision and recall values) with BTC-CBIR methods using luminance-chrominance color spaces (YCgCb, Kekre’s LUV, YUV, YIQ, YCbCr) as compared to non-luminance (RGB, HSI, HSV, rgb , XYZ) Color spaces. The performance of multileveled BTC-CBIR increases gradually with increase in level up to certain extent (Level 3) and then increases slightly due to voids being created at higher levels. In all levels of BTC Kekre’s LUV color space gives best performance

Improving Performance of Multileveled BTC Based CBIR Using Sundry Color Spaces

CSCJournals

IEEE Projects 2014-2015

Finalyear Projects

CBIR For Medical Imaging...

Isha Sharma

The current study deals with deriving of image feature descriptor by error diffusion based block truncation coding (EDBTC). The image feature descriptor is basically comprised by the two error diffusion block truncation coding, color quantizers and its equivalent bitmap image. The bitmap image distinguish the image edges and textural information of two color quantizers to signify the color allocation and image contrast derived by the Bit Pattern Feature and Color Co-occurrence Feature. Tentative outcome reveal the benefit of proposed feature descriptor as contrast to existing schemes in image retrieval assignment under normal and textural images. The Error-Diffusion Block Truncation Coding method compresses an image efficiently, and at the same time, its consequent compacted information flow can provides an efficient feature descriptor intended for operating image recovery and categorization. As a result, the proposed design preserves an effective candidate for real-time image retrieval applications.

Retrieval of Images Using Color, Shape and Texture Features Based on Content

rahulmonikasharma

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.

Content Based Image Retrieval Approach Based on Top-Hat Transform And Modifie...

cscpconf

CBIR by deep learning

Vigen Sahakyan

Cbir final ppt

rinki nag

Content based image retrieval based on shape with texture features

Alexander Decker

Content based image retrieval using clustering Algorithm(CBIR)

Raja Sekar

Week06 bme429-cbir

Ikram Moalla

Content-based Image Retrieval

University of Zurich

Content Based Image Retrieval

Rayan Dasoriya

Content Based Image Retrieval

Prem kumar

In this paper, we present a novel approach for image retrieval based on extraction of low level features using techniques such as Directional Binary Code (DBC), Haar Wavelet transform and Histogram of Oriented Gradients (HOG). The DBC texture descriptor captures the spatial relationship between any pair of neighbourhood pixels in a local region along a given direction, while Local Binary Patterns (LBP) descriptor considers the relationship between a given pixel and its surrounding neighbours. Therefore, DBC captures more spatial information than LBP and its variants, also it can extract more edge information than LBP. Hence, we employ DBC technique in order to extract grey level texture features (texture map) from each RGB channels individually and computed texture maps are further combined which represents colour texture features (colour texture map) of an image. Then, we decomposed the extracted colour texture map and original image using Haar wavelet transform. Finally, we encode the shape and local features of wavelet transformed images using Histogram of Oriented Gradients (HOG) for content based image retrieval. The performance of proposed method is compared with existing methods on two databases such as Wang’s corel image and Caltech 256. The evaluation results show that our approach outperforms the existing methods for image retrieval.

Low level features for image retrieval based

caijjournal

Our goal of the project is to develop a complete, fully detailed 3D interactive model of the human body and systems in the human body, and allow the user to interacts in 3D with all the elements of that system, to teach students about human anatomy. Some organs, which contain a lot of details about a particular anatomy, need to be accurately and fully described in minute detail, such as the brain, lungs, liver and heart. These organs are need have all the detailed descriptions of the medical information needed to learn how to do surgery on them, and should allow the user to add careful and precise marking to indicate the operative landmarks on the surgery location. Adding so many different items of information is challenging when the area to which the information needs to be attached is very detailed and overlaps with all kinds of other medical information related to the area. Existing methods to tag areas was not allowing us sufficient locations to attach the information to. Our solution combines a variety of tagging methods, which use the marking method by selecting the RGB color area that is drawn in the texture, on the complex 3D object structure. Then, it relies on those RGB color codes to tag IDs and create relational tables that store the related information about the specific areas of the anatomy. With this method of marking, it is possible to use the entire set of color values (R, G, B) to identify a set of anatomic regions, and this also makes it possible to define multiple overlapping regions.

An effective RGB color selection for complex 3D object structure in scene gra...

IJECEIAES

Content-based Image Retrieval is all about generating signatures of images in database and comparing the signature of the query image with these stored signatures. Color histogram can be used as signature of an image and used to compare two images based on certain distance metric. Distance metrics Manhattan distance (L1 norm) and Euclidean distance (L2 norm) are used to determine similarities between a pair of images. In this paper, Corel database is used to evaluate the performance of Manhattan and Euclidean distance metrics. The experimental results showed that Manhattan showed better precision rate than Euclidean distance metric. The evaluation is made using Content based image retrieval application developed using color moments of the Hue, Saturation and Value(HSV) of the image and Gabor descriptors are adopted as texture features.

Evaluation of Euclidean and Manhanttan Metrics In Content Based Image Retriev...

IJERA Editor

What's hot (20)

Literature Review on Content Based Image Retrieval

Content-Based Image Retrieval Features: A Survey

CBIR

Content Based Image and Video Retrieval Algorithm

Improving Performance of Multileveled BTC Based CBIR Using Sundry Color Spaces

IEEE Projects 2014-2015

CBIR For Medical Imaging...

Retrieval of Images Using Color, Shape and Texture Features Based on Content

Content Based Image Retrieval Approach Based on Top-Hat Transform And Modifie...

CBIR by deep learning

Cbir final ppt

Content based image retrieval based on shape with texture features

Content based image retrieval using clustering Algorithm(CBIR)

Week06 bme429-cbir

Content-based Image Retrieval

Content Based Image Retrieval

Low level features for image retrieval based

An effective RGB color selection for complex 3D object structure in scene gra...

Evaluation of Euclidean and Manhanttan Metrics In Content Based Image Retriev...

Similar to Content based image retrieval using features extracted from halftoning-based block truncation coding

Content based image retrieval using error diffusion block truncation coding f...

LogicMindtech Nologies

A technique for Content Based Image Retrieval (CBIR) for the generation of image content descriptor which exploiting the advantage of low complexity Order Dither Block Truncation Coding (ODBTC). The quantizer and bitmap image are the compressed form of image obtained from the ODBTC technique in encoding step. Decoding is not performed in this method. It has two image feature such as Color Co-occurrence Feature (CCF) and Bit Pattern Feature (BPF) for indexing the image. These features are directly obtained from ODBTC encoded data stream. By comparing with the BTC image retrieval system and other earlier method the experimental result show the proposed method is superior. ODBTC is suited for image compression and it is a simple and effective descriptor to index the image in CBIR system. Content-based image retrieval is a technique which is used to extract the images on the basis of their content such as texture, color, shape and spatial layout. In order to minimize this gap many concepts was introduced. Moreover, Images can be stored and extracted based on various features and one of the prominent feature is Texture.

Feature Extraction in Content based Image Retrieval

ijcnes

Image Retrieval Based on its Contents Using Features Extraction

IRJET Journal

This paper presents a new halftoning-based block truncation coding (HBTC) image reconstruction using sparse representation framework. The HBTC is a simple yet powerful image compression technique, which can effectively remove the typical blocking effect and false contour. Two types of HBTC methods are discussed in this paper, i.e., ordered dither block truncation coding (ODBTC) and error diffusion block truncation coding (EDBTC). The proposed sparsity-based method suppresses the impulsive noise on ODBTC and EDBTC decoded image with a coupled dictionary containing the HBTC image component and the clean image component dictionaries. Herein, a sparse coefficient is estimated from the HBTC decoded image by means of the HBTC image dictionary. The reconstructed image is subsequently built and aligned from the clean, i.e. non-compressed image dictionary and predicted sparse coefficient. To further reduce the blocking effect, the image patch is firstly identified as “border” and “non-border” type before applying the sparse representation framework. Adding the Laplacian prior knowledge on HBTC decoded image, it yields better reconstructed image quality. The experimental results demonstrate the effectiveness of the proposed HBTC image reconstruction. The proposed method also outperforms the former schemes in terms of reconstructed image quality.

Halftoning-based BTC image reconstruction using patch processing with border ...

TELKOMNIKA JOURNAL

Adaptive CSLBP compressed image hashing

IJECEIAES

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.

Research Inventy : International Journal of Engineering and Science

researchinventy

As with the advancement of multimedia technologies, users are not gratified with the conventional retrieval system techniques. So a application “Content Based Image Retrieval System” is introduced. CBIR is the application to retrieve the images or to search the digital images from the large database .The term “content” deals with the colour, shape, texture and all the information which is extracted from the image itself. This paper reviews the CBIR system which uses SVM classifier based algorithms for feature extraction phase.

A Review of Feature Extraction Techniques for CBIR based on SVM

IJEEE

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.

IJET-V2I6P17

IJET - International Journal of Engineering and Techniques

Self-Directing Text Detection and Removal from Images with Smoothing

Priyanka Wagh

The aim of this paper is to present a comparative study of two linear dimension reduction methods namely PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis). The main idea of PCA is to transform the high dimensional input space onto the feature space where the maximal variance is displayed. The feature selection in traditional LDA is obtained by maximizing the difference between classes and minimizing the distance within classes. PCA finds the axes with maximum variance for the whole data set where LDA tries to find the axes for best class seperability. The neural network is trained about the reduced feature set (using PCA or LDA) of images in the database for fast searching of images from the database using back propagation algorithm. The proposed method is experimented over a general image database using Matlab. The performance of these systems has been evaluated by Precision and Recall measures. Experimental results show that PCA gives the better performance in terms of higher precision and recall values with lesser computational complexity than LDA

SIGNIFICANCE OF DIMENSIONALITY REDUCTION IN IMAGE PROCESSING

sipij

The aim of this paper is to present a comparative s tudy of two linear dimension reduction methods namely PCA (Principal Component Analysis) a nd LDA (Linear Discriminant Analysis). The main idea of PCA is to transform the high dimen sional input space onto the feature space where the maximal variance is displayed. The featur e selection in traditional LDA is obtained by maximizing the difference between classes and mi nimizing the distance within classes. PCA finds the axes with maximum variance for the whole data set where LDA tries to find the axes for best class seperability. The proposed method is experimented over a general image database using Matlab. The performance of these systems has been evaluated by Precision and Recall measures. Experimental results show that PCA based dimension reduction method gives the better performance in terms of higher precision and recall values with lesser computational complexity than the LDA based method.

C OMPARATIVE S TUDY OF D IMENSIONALITY R EDUCTION T ECHNIQUES U SING PCA AND ...

csandit

In real-world applications, service robots need to locate and identify objects in a scene. A range sensor provides a robust estimate of depth information, which is useful to accurately locate objects in a scene. On the other hand, color information is an important property for object recognition task. The objective of this paper is to detect and localize multiple objects within an image using both range and color features. The proposed method uses 3D shape features to generate promising hypotheses within range images and verifies these hypotheses by using features obtained from both range and color images.

Object detection for service robot using range and color features of an image

IJCSEA Journal

3.[18 30]graph cut based local binary patterns for content based image retrieval

Alexander Decker

OBJECT DETECTION FOR SERVICE ROBOT USING RANGE AND COLOR FEATURES OF AN IMAGE

IJCSEA Journal

Object Detection for Service Robot Using Range and Color Features of an Image

IJCSEA Journal

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.

D43031521

IJERA Editor

CBIR Processing Approach on Colored and Texture Images using KNN Classifier a...

IRJET Journal

Image hashing is an efficient way to handle digital data authentication problem. Image hashing represents quality summarization of image features in compact manner. In this paper, the modified center symmetric local binary pattern (CSLBP) image hashing algorithm is proposed. Unlike CSLBP 16 bin histogram, Modified CSLBP generates 8 bin histogram without compromise on quality to generate compact hash. It has been found that, uniform quantization on a histogram with more bin results in more precision loss. To overcome quantization loss, modified CSLBP generates the two histogram of a four bin. Uniform quantization on a 4 bin histogram results in less precision loss than a 16 bin histogram. The first generated histogram represents the nearest neighbours and second one is for the diagonal neighbours. To enhance quality in terms of discrimination power, different weight factor are used during histogram generation. For the nearest and the diagonal neighbours, two local weight factors are used. One is the Standard Deviation (SD) and other is the Laplacian of Gaussian (LoG). Standard deviation represents a spread of data which captures local variation from mean. LoG is a second order derivative edge detection operator which detects edges well in presence of noise. The proposed algorithm is resilient to the various kinds of attacks. The proposed method is tested on database having malicious and non-malicious images using benchmark like NHD and ROC which confirms theoretical analysis. The experimental results shows good performance of the proposed method for various attacks despite the short hash length.

Modified CSLBP

IJECEIAES

11.graph cut based local binary patterns for content based image retrieval

Alexander Decker

3.[18 30]graph cut based local binary patterns for content based image retrieval

Alexander Decker

Recently uploaded

From customer value engagements to hands-on production support, our Services span across every stage of our customers digital transformation journey, to help ensure that every customer is successful in their adoption of our solutions. • Implementation, Upgrade, Migration, and Maintenance Services • On-Premises and On-Cloud • COTS Training Services; On-Site and Virtual • Software Support Services; Legacy and 3DEXPERIENCE • Value Engagement & Blueprinting • Specialized Consulting and Support Services • Customized Training Services • Automation and Configuration Services • Technical Resource Augmentation Services • Project Management • Know-how Training (mentoring) and Resource Augmentation

Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...

Arindam Chakraborty, Ph.D., P.E. (CA, TX)

DeepFakes presentation : brief idea of DeepFakes

MayuraD1

PE 459 LECTURE 2- natural gas basic concepts and properties

sarkmank1

Unleashing the Power of the SORA AI lastest leap

RishantSharmaFr

The project Hospital Management system includes registration of patients, storing their details into the system, and also computerized billing in the pharmacy, and labs. The software has the facility to give a unique id for every patient and stores the details of every patient and the staff automatically. It includes a search facility to know the current status of each room. User can search availability of a doctor and the details of a patient using the id. The Hospital Management System can be entered using a username and password. It is accessible either by an administrator or receptionist. Only they can add data into the database. The data can be retrieved easily. The interface is very user-friendly. The data are well protected for personal use and makes the data processing very fast. Hospital Management System is powerful, flexible, and easy to use and is designed and developed to deliver real conceivable benefits to hospitals. Hospital Management System is designed for multispecialty hospitals, to cover a wide range of hospital administration and management processes. It is an integrated end-to-end Hospital Management System that provides relevant information across the hospital to support effective decision making for patient care, hospital administration and critical financial accounting, in a seamless flow. Hospital Management System is a software product suite designed to improve the quality and management of hospital management in the areas of clinical process analysis and activity-based costing. Hospital Management System enables you to develop your organization and improve its effectiveness and quality of work. Managing the key processes efficiently is critical to the success of the hospital helps you manage your processes.

Hospital management system project report.pdf

Kamal Acharya

Computer Networks Basics of Network Devices

ChandrakantDivate1

"Lesotho Leaps Forward: A Chronicle of Transformative Developments"

mphochane1998

Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil

Cara Menggugurkan Kandungan 087776558899

FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads

Arindam Chakraborty, Ph.D., P.E. (CA, TX)

Engineering Drawing focus on projection of planes

RAJNEESHKUMAR341697

Thermal Engineering-R & A / C - unit - V

DineshKumar4165

In the dynamic landscape of energy storage, choosing the right battery pack is a critical decision that significantly impacts performance, efficiency, and overall product design. This webinar aims to unravel the complexities surrounding standard and custom battery packs (primarily lithium), providing you with a comprehensive understanding to make informed decisions. We'll embark on a journey to explore the fundamental distinctions between standard off-the-shelf battery packs and their bespoke counterparts tailored to specific applications. We will delve into the nuance of what is defined as a standard battery pack along with its benefits, limitations, and how it caters to broad market needs. Simultaneously, we will dissect the world of custom battery packs, diving into the advantages they offer in terms of precise energy requirements, form factors, and unique design considerations. Whether you are a product designer, engineer, or industry professional, this webinar is designed to equip you with the knowledge necessary to navigate the intricate terrain of battery pack selection. Join us for this webinar as we navigate through the intricacies of standard and custom battery packs, empowering you to make strategic decisions that align with your project goal. For more information on our battery pack solutions, visit https://www.epectec.com/batteries/.

Standard vs Custom Battery Packs - Decoding the Power Play

Epec Engineered Technologies

STEAM NOZZLES AND TURBINES Flow of steam through nozzles, shapes of nozzles, effect of friction, critical pressure ratio, supersaturated flow - impulse and reaction principles, velocity diagram, work done and efficiency – types of compounding - governors. AIR COMPRESSORS Classification - working principle - type of compressors, work of compression with and without clearance - volumetric efficiency - isothermal and isentropic efficiency of reciprocating compressors - multistage air compressor with inter cooling.

Thermal Engineering -unit - III & IV.ppt

DineshKumar4165

Education system forms the backbone of every nation. And hence it is important to provide a strong educational foundation to the young generation to ensure the development of open-minded global citizens securing the future for everyone. Advanced technology available today can play a crucial role in streamlining education-related processes to promote solidarity among students, teachers and the school staff. School Management System(SMS) consists of tasks such as registering students, attendance record keeping to control absentees, producing report cards, producing official transcript, preparing timetable and producing different reports for teachers, officials from Dr.Mohiuddin Education foundation and other stakeholders. Automation is the utilization of technology to replace human with a machine that can perform more quickly and more continuously. By automating SMS documents that took up many large storage rooms can be stored on few disks. Transcript images can be annotate. It reduces the time to retrieve old transcripts from hours to seconds.

School management system project Report.pdf

Kamal Acharya

Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRLS IN bhubaneswar ESCORT SERVICE❤CALL GIRL No Advance Pay 💋💋 Book Now +91-9777949614 Discover Bhubaneswar Finest Call GirlsY ou're heading to Bhubaneswar for business or pleasure and want to experience the city to the fullest. What better way than in the company of a beautiful, intelligent companion to show you around town? Look no further than Bhubaneswar's finest Call Girls. These lovely ladies know all the hot spots and hidden gems that only locals are privy to. From the top restaurants and bars to the most stunning sights, they'll ensure you make unforgettable memories.

Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...

Call Girls Mumbai

A Study of Urban Area Plan for Pabna Municipality

Morshed Ahmed Rahath

Saudi Arabia [ Abortion pills) Jeddah/riaydh/dammam/+918761049707☎️] cytotec tablets uses abortion pills 💊💊 How effective is the abortion pill? 💊💊 +918761049707) "Abortion pills in Jeddah" how to get cytotec tablets in Riyadh " Abortion pills in dammam*💊💊 The abortion pill is very effective. If you’re taking mifepristone and misoprostol, it depends on how far along the pregnancy is, and how many doses of medicine you take:💊💊 +918761049707) how to buy cytotec pills At 8 weeks pregnant or less, it works about 94-98% of the time. +918761049707[ 💊💊💊 At 8-9 weeks pregnant, it works about 94-96% of the time. +918761049707) At 9-10 weeks pregnant, it works about 91-93% of the time. +918761049707)💊💊 If you take an extra dose of misoprostol, it works about 99% of the time. At 10-11 weeks pregnant, it works about 87% of the time. +918761049707) If you take an extra dose of misoprostol, it works about 98% of the time. In general, taking both mifepristone and+918761049707 misoprostol works a bit better than taking misoprostol only. +918761049707 Taking misoprostol alone works to end the+918761049707 pregnancy about 85-95% of the time — depending on how far along the+918761049707 pregnancy is and how you take the medicine. +918761049707 The abortion pill usually works, but if it doesn’t, you can take more medicine or have an in-clinic abortion. +918761049707 When can I take the abortion pill?+918761049707 In general, you can have a medication abortion up to 77 days (11 weeks)+918761049707 after the first day of your last period. If it’s been 78 days or more since the first day of your last+918761049707period, you can have an in-clinic abortion to end your pregnancy.+918761049707 Why do people choose the abortion pill? Which kind of abortion you choose all depends on your personal+918761049707preference and situation. With+918761049707medication+918761049707 abortion, some people like that you don’t need to have a procedure in a doctor’s office. You can have your medication abortion on your own+918761049707schedule, at home or in another comfortable place that you choose.+918761049707 You get to decide who you want to be with during your abortion, or you can go it alone. Because+918761049707medication abortion is similar to a miscarriage, many people feel like it’s more “natural” and less invasive. And some+918761049707 people may not have an in-clinic abortion provider close by, so abortion pills are more available to+918761049707 them. +918761049707 Your doctor, nurse, or health center staff can help you decide which kind of abortion is best for you. More questions from patients: Saudi Arabia+918761049707 CYTOTEC Misoprostol Tablets. Misoprostol is a medication that can prevent stomach ulcers if you also take NSAID medications. It reduces the amount of acid in your stomach, which protects your stomach lining. The brand name of this medication is Cytotec®️.+918761049707) Unwanted Kit is a combination of two medicines, which is used for

Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwait

jaanualu31

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

ssuser89054b

GAS POWER CYCLES Cycles: Otto, Diesel, Dual, Brayton - Calculation of mean effective pressure - Air standard efficiency - Comparison of cycles INTERNAL COMBUSTION ENGINES Classification - Components and their function - valve timing diagram and port timing diagram - actual and theoretical p-v diagram of two stroke and four stroke engines – carburettor - diesel pump and injector system - battery and magneto ignition system - principles of combustion and detonation in CI engines - lubrication and cooling systems - performance parameters and calculations.

Thermal Engineering Unit - I & II . ppt

DineshKumar4165

Moment Distribution Method For Btech Civil

VinayVitekari

Recently uploaded (20)

Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...

DeepFakes presentation : brief idea of DeepFakes

PE 459 LECTURE 2- natural gas basic concepts and properties

Unleashing the Power of the SORA AI lastest leap

Hospital management system project report.pdf

Computer Networks Basics of Network Devices

"Lesotho Leaps Forward: A Chronicle of Transformative Developments"

Cara Menggugurkan Sperma Yang Masuk Rahim Biyar Tidak Hamil

FEA Based Level 3 Assessment of Deformed Tanks with Fluid Induced Loads

Engineering Drawing focus on projection of planes

Thermal Engineering-R & A / C - unit - V

Standard vs Custom Battery Packs - Decoding the Power Play

Thermal Engineering -unit - III & IV.ppt

School management system project Report.pdf

Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...

A Study of Urban Area Plan for Pabna Municipality

Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwait

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Thermal Engineering Unit - I & II . ppt

Moment Distribution Method For Btech Civil

Content based image retrieval using features extracted from halftoning-based block truncation coding

1. Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Title: Effective Image Retrieval System Using Dot-Diffused Block Truncation Coding Features Abstract—This paper presents a new approach to derive the image feature descriptor from the dot-diffused block truncation coding (DDBTC) compressed data stream. The image feature descriptor is simply constructed from two DDBTC representative color quantizers and its corresponding bitmap image. The color histogram feature (CHF) derived from two color quantizers represents the color distribution and image contrast, while the bit pattern feature (BPF) constructed from the bitmap image characterizes the image edges and textural information. The similarity between two images can be easily measured from their CHF and BPF values using a specific distance metric computation. Experimental results demonstrate the superiority of the proposed feature descriptor compared to the former existing schemes in image retrieval task under natural and textural images. The DDBTC method compresses an image efficiently, and at the same time, its corresponding compressed data stream can provide an effective feature descriptor for performing image retrieval and classification. Consequently, the proposed scheme can be considered as an effective candidate for real-time image retrieval applications.

2. Software & Hardware requirement: 1. Hardware requirement: 1. PC 2. RAM minimum 2GB 3. HDD minimum 100GB 2. Software requirement: 1. MATLAB 7.0 2. Signal processing toolbox 3. Image processing toolbox 4. Mathematical toolbox PROJECT FLOW: First Review: Literature Survey Paper Explanation Design of Project Project Enhancement explanation Second Review: Implementing 40% of Base Paper Third Review Implementing Remaining 60% of Base Paper with Future Enhancement (Modification) For More Details please contact Logic Mind Technologies Vijayangar (Near Maruthi Medicals), Bangalore-40 Ph: 8123668124 // 8123668066 Mail: logicmindtech@gmail.com

Content based image retrieval using features extracted from halftoning-based block truncation coding

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Content based image retrieval using features extracted from halftoning-based block truncation coding

Similar to Content based image retrieval using features extracted from halftoning-based block truncation coding (20)

More from LogicMindtech Nologies

More from LogicMindtech Nologies (20)

Recently uploaded

Recently uploaded (20)

Content based image retrieval using features extracted from halftoning-based block truncation coding