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jamzad--mansour
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Total 93 records
Human Activity Recognition with Spatio Temporal Features in RGB-D Videos
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Human activity recognition is an important and useful area in computer vision that application include surveillance systems, patient monitoring systems, human-computer interaction and analyse video data from big websites.Traditional Human action recognition use the RGB videos as default input that unable describe motion and action as full. On the other hand Kinect camera sendsthe RGB data to output in addition to the Depth Data that allows us to extract skeleton of human easily. Recently Space-time features have been particulary popular in RGB Videos because of their structure. These features are describedby their descriptor and send the good and important information to output.Finally we...
Automatic Image Annotation Using Deep Learning
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
With the advances in technology, Nowadays digital cameras are everywhere. As a result very large amount of images are on the web. Searching through these images intelligently and purposively is an essential need. Recently the possibility of retrieving images with some conceptual words along side of content based image retrieval has been studied in computer vision. For this purpose it’s required that for each image several words that describe its content be assigned automatically. One of the main problems for this task is semantic gap, meaning that the low level features such as color, texture,… don’t have the ability to describe the high level concepts in images which are comprehensible by...
Automatic Skin Cancer (Melanoma) Detection Using Visual Features
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Melanoma is a malignant skin cancer which is caused by cancerous growth of melanocytes. If not treated at its early development stages, melanoma is the deadliest form of cancer. The best way to cure melanoma is to treat it in its earliest stage of development. Since a melanoma leasion is similar to benign moles (regaring its shape and appearance) at its early stages of development, it is often mistaken for moles and left untreated. Therefore, automatic melanoma detection can increase the survival rate of patients by detecting melanoma in its early stages. In this thesis, a new method for automatic diagnosis of melanoma using segmented dermoscopic images is provided. Almost all related...
Improving Watermarking Robustness Against Print and Scan Attack
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
The advent of digital age with the Internet revolution has made it extremely convenient for users to access, create, process, copy, or exchange multimedia data. This has created an urgent need for protecting intellectual property in both the digital and the print media. Digital watermarking is a suitable way to do this. In this technology, some hidden information called watermark are embedded into host signal and extracted to confirm copyright protection. However, the watermark should be embedded in the host in such a way that the attacks could not destroy it. Print and scan is a popular attack that is applied on digital images. This attack has complex nature and can be implemented easily....
Improving the Embedding Capacity of Steganography Methods
, Ph.D. Dissertation Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Providing security for digital information in a communication channel is a challenge in the recent years. This is due to the strength of high-speed processing resources that can threaten the security and correctness of communicating information. Using steganography method, the secret information can be hidden in an innocent media that does not attract the attention of third parties. This research discusses about steganography in images. The main goal of this research is presenting a universal steganography scheme with high steganography capacity. Using this scheme the steganographer can embed every large secret data in images securely. The reasons for selecting the subject of “Improving...
Tamper Detection in Digital Images Using Transform Domains
,
M.Sc. Thesis
Sharif University of Technology
;
Jamzad, Mansour
(Supervisor)
Abstract
Nowadays, digital images are easy to manipulate and edit due to availability of powerful image processing and editing software. It is possible to add or remove important features to the image without leaving any obvious traces of tampering. Therefore, proving the authenticity and integrity of digital media becomes increasingly important. In this study, we focus on detection of a special type of digital forgery, the copy-move attack, in which a part of the image is copied and pasted somewhere else in the image with the intent to cover an important image features or to add some fake feature. In this way we propose some novel methods that work in spatial domain, Discrete Cosine domain and...
Improving the Robustness of Image Watermarking for Publicly Copyright-Proving
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
The advent of Internet and advancement of computer technologies have enabled convenient and fast exchange of multimedia so the illegal reproduction and modification of digital media has become increasingly serious. Hence, how to protect the intellectual property rights of digital multimedia is an imperative issue. Digital watermarking is one of the solutions to prevent unauthorized use of images. Traditional digital watermarking techniques embed a watermark such as logo, trademark, or copyright information into a host image so that it is not perceptible. These techniques, depending on the amount of embedded data, will distort the content of host image which results in quality degradation of...
A Hybrid Method for Improving the Color Constancy in Images
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
The ability of measuring colors of objects, independent of light source illumination, is called color constancy which is an important field in machine vision and image processing. In this thesis, we propose five new combinantional ways in color constansy fields. The first two proposed methods use neural networks to combining basic methods. The third and forth proposed methods use fuzzy measures and integrals for combining color constancy methods. And finally fifth method combines methods with indoor outdoor classification this method has the best result (3.01 median angular error) in proposed methods and past methods in color constancy fields. It is shown in this article that the proposed...
A Fast Algorithm for Shadow Generation with Low Distortion Based on Shadow Map Technique
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Shadows are one of the most important details in graphical images. There exist many shadow generation algorithms each of which suffers from some problems. High processing time and ill-shaped shadow borders, known as alasing, are some of such problems. In this paper, we propose a heuristic method based on standard shadow map technique, named rotated shadow maps, to generate excellent hard shadows. Our method uses some shadow maps which are generated from the same view but objects are slightly rotated around the center of view area. Rotated shadow maps can be considered as an independent hard shadow generation algorithm. Also it can be combined with other shadow map based approaches. Utilizing...
Indoor Office Environment Mapping Using a Mobile Robot with Kinect Sensor
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
In recent years with advancement of Robotics, the applications of wide scale use of robots in our homes is not as far-fetched as it was before. One of the important problems for an indoor robot is moving inside a new and unknown environment. To achieve this, the robot should, with the help of its sensors, not only calculate its location; but should also build a map of the environment for later use. Additionally, the robot must be able to explore this unknown environment. The most important drawbacks of the classical solutions to these problems are long computation times, heavy memory usage and absence of precision. In recent years, large amount of research effort has put on solving these...
Image Annotation Using Semi-supervised Learning
, Ph.D. Dissertation Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Aautomatic image annotation that assigns some labels to input images and provides a textual description for the contents of images has become an active field in machine vision community. To design an annotation system, we need a dataset that contains images and labels for them. However, a large amount of manual efforts is required to annotate all images in a dataset. To reduce the demand of annotation systems on the labeled images, one solution is to exploit useful information embedded into the unlabeled images and incorporate them into learning process. In machine learning community, semi-supervised learning (SSL) has been introduced with the aim of incorporating unlabeled samples into the...
Steganalysis Method Based on Image Class
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Steganalysis is the art of detecting hidden message in a cover such as an image. All steganalysis methods either are designed for a specific steganographer or are blind. Since for a stego image, the steganography method is not available, this is important to detect a stego image without any knowledge about the steganography method using which the secret image was embedded. Therefore in order to dominate all steganography method, if a given image is a stego one, we need to use voting over several steganalysis methods applied on the stego image to improve the accuracy of detection. But this approach needs a long time to process that is not practical for most steganalysis applications. We know...
Face Motion Capture using a Regular Camera and Constructing face 3D Graphical Model
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
In this project, using one regular color camera, a video is captured of an actor’s face. Using machine vision and without any kind of markers on the actor’s face, this video is processed to extract the locations of some desired points on the face of the actor. Then these points are mapped to corresponding points on a 3D graphical model of a face, so that a realistic animation of facial movements is achieved. The extracted points, including points on the eyebrows, eyes and lips are the most important ones for the purpose of facial animation. To extract these points, in each region several methods are implemented and studied to find the best method, finally for extracting points on the...
Dynamic Motion Planning and Obstacle Avoidance Simulation for Autonomous Robot-car in Webots
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Motion planning in an autonomous vehicle is responsible for providing smooth, safe and efficient actions. Besides reducing the risk of collision with static and moving obstacles, the ability to make suitable decisionsencountering sudden changes in environment is very important. Many solutions for dealing this problem have been offered, one of which is, Artificial Potential Fields (APF). APF is a simple and computationally low cost method which keeps the robot away from the obstacles in the environment. However, this approach suffers from trapping in local minima’s of potential function and then fails to produce a plan. Furthermore,Oscillation in presence of obstacles or in narrow passages...
Extracting Appropriate Features for Zero Watermarking of Similar Images for Ownership Protection
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Digital watermarking is an efficacious technique to protect the copyright and ownership of digital information. Traditional image watermarking algorithms embed a logo in the image that could reduce its visual quality. A new approach in watermarking called zero watermarking doesn’t need to embed a logo in the image. In this algorithm we find a feature from the main image and combine it with a logo to obtain a key. This key is securely kept by a trusted authority. In this thesis we show that we can increase the robustness of digital zero watermarking by a new counter detection method in comparison to Canny Edge detection and morphological dilatation that is mostly used by related works....
Improving the Performance of Distributed Fusion for PHD Filter in Multi-Object Tracking
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
The Gaussian mixture (cardinalized) probability hypothesis density (GM-(C)PHD) filter is a closed form approximation of multi-target Bayes filter which can overcome most of multi-target tracking problems. Limited field of view, decreasing cost of cameras and its advances induce us to use large-scale camera networks. Increasing the size of camera networks make centralized networks practically inefficient. On the other hand, scalability, simplicity and low data transmission cost has made distributed networks a good replacement for centralized networks. However, data fusion in distributed network is sub-optimal due to unavailable cross-correlation.Among data fusion algorithms which deal with...
Images Classification with Limited Number of Labeled Data Using Domain Adaptation
, M.Sc. Thesis Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
The traditional machine learning methods assume that the training data and the test data are drawn from the same distribution (or drawn from the same domain). In practice, in many computer vision applications, this assumption may not hold. Unfortunately, the performance of these methods degrades on dataset drawn from a different domain. Domain adaptation attempts to minimize this degradation caused by distribution mismatch between the training and test data. Domain adaptation tries to adapt a model trainded from one domain to another domain. We focus on supervised domain adaptation method in which limited labeled data is available from the target domain. We propose a new domain adaptation...
Content Based Image Retrieval Using Segmentation Similarity Measure
,
M.Sc. Thesis
Sharif University of Technology
;
Jamzad, Mansour
(Supervisor)
Abstract
Content Based Image Retrieval (CBIR) is a research area in computer vision. This area comprises of two main steps, low level feature extraction such as color, texture and shape extraction and also similarity measures for comparison of images. The challenge in this system is the existence semantic gap between the low level visual features and the high level image semantics. The aim of research in this field is to reduce this semantic gap. In this study the images are divided into regions using Meanshift method, for color segmentation and then moments of each region as color feature are calculated. Also for extracting texture the images are divided into regions using Jseg method, and then...
Automatic Image Annotation by Multi-view Non-negative Matrix Factorization
, Ph.D. Dissertation Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
Nowadays the number of digital images has largely increased because of progress in internet technology. Management of this volume of data needs an efficient system for browsing, categorizing, and searching the images. The goal of this research is to design a system for automatic annotation of unobserved images for better search in image data bases. Automatic image annotation is a multi-label classification problem with many labels which suggests some words for describing the content of an image. Designing AIA systems faces chanllenges like semantic gap between low level image features and high level human expressions (tags), incompelete tags and imbalance images per tags in the datasets....
Localized Multiple Kernel Learning for Image Classification
, Ph.D. Dissertation Sharif University of Technology ; Jamzad, Mansour (Supervisor)
Abstract
It is not possible to compute a linear classifier to classify real world images, which are the focus of this thesis. Therefore, the space of such images is considered as a complex. In such cases, kernel trick in which data samples are implicitly mapped to a higher dimension space, leads to a more accurate classifier in such spaces. In kernel learning methods, the best kernel is trained for the classification problem in hand. Multiple Kernel Learning is a framework which uses weighted sum of multiple kernels. This framework achieves good accuracy in image classification since it allows describing images via various features. In the image input space which is composed of different extracted...