Sharif Digital Repository

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... 

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... 

Setar is a traditional Persian musical instrument. Nowadays, Setar is one of the most common musical instruments in Persian music. A systematic method for Setar production modification has not been introduced yet. This work is the first scientific work about analysis of this instrument. The aim of this study is to undertake early steps for Setar quality improvement. In this thesis, after analysis of the wood using in Setar construction, numerical and experimental methods have been utilized to analyze this instrument. After that, some works has been performed to extract an objective function which can judge about Setar quality. The results show good agreement between experimental and... 

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... 

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... 

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... 

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... 

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... 

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... 

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 (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... 

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.... 

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... 

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... 

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... 

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...