Sharif Digital Repository

Color information of natural images can be considered as a highly correlated vector space. Many different color spaces have been proposed in the literature with different motivations toward modeling and analysis of this stochastic field. Recently, color transfer among different images has been under investigation. Color transferring consists of two major categories: colorizing grayscale images and recoloring colored images. The literature contains a few color transfer methods that rely on some standard color spaces. In this paper, taking advantages of the principal component analysis (PCA), we propose a unifying framework for both mentioned problems. The experimental results show the... 

Color image segmentation is a primitive operation in many image processing and computer vision applications. Accordingly, there exist numerous segmentation approaches in the literature, which might be misleading for a researcher who is looking for a practical algorithm. While many researchers are still using the tools which belong to the old color space paradigm, there is evidence in the research established in the eighties that a proper descriptor of color vectors should act locally in the color domain. In this paper, these results are used to propose a new color image segmentation method. The proposed method searches for the principal colors, defined as the intersections of the cylindrical... 

From the birth of multi-spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray-scale images, instead of an ensemble of an n-D realization. However, it has been proved that using vector-based tools leads to a more appropriate understanding of color images and thus more efficient algorithms for processing them. Such tools are able to take into consideration the high correlation of the color components and thus to successfully carry out energy compaction. In this paper, a novel method is proposed to utilize the principal component analysis in the neighborhoods of an image in order to extract the corresponding eigenimages.... 

Transmission of video over error prone and still bandwidth limited wireless channels demand high compression efficiency and resilience to packet losses and errors. Scalable or layered video coding applied to highly compression efficient codecs is an ideal solution to the problem. However, scalability reduces compression efficiency of the coders. In this paper we show how compression efficiency of two-layer SNR scalable video coders can be retained via joint base-enhancement layer optimization. Simulation results show that joint base-enhancement layer optimization significantly outperforms separate optimization of the layers, and it closely follows the compression performance of the... 

In content based image retrieval similarity measurement is one of the most important aspects in a large image database for efficient search and retrieval to find the best answer for a user query. Color and texture are among the more expressive of the visual features. Considerable work has been done in designing efficient descriptors for these features for applications such as similarity retrieval. The MPEG-7 specifies a standard set of descriptors for color, texture and shape. In the Human Vision System (HVS), visual information is not perceived equally; some information may be more important than other information. The purpose of this paper is to show how the MPEG-7 descriptor based on... 

The ubiquity of broadband digital communications and mass storage in modern society has stimulated the widespread acceptance of digital media. However, easy access to royalty-free digital media has also resulted in a reduced perception in society of the intellectual value of digital media and has promoted unauthorised duplication practices. To detect and discourage the unauthorised duplication of media, researchers have investigated watermarking methods to embed ownership data into media. However, some authorities have expressed doubt over the efficacy of watermarking methods to protect digital media. The paper introduces a novel method to discourage unauthorised duplication of digital... 

A significant step in color image compression is to apply a color space transformation to the original RGB image to concentrate most of its energy in one plane. Standard JPEG-based compression methods utilize predefined transformations like RGB to YCbCr. In this paper, a devised algorithm is proposed to optimize the transformation for each image. The algorithm iteratively increases the energy concentration by optimizing a novel cost function while limiting the matrix determinant to a bounded region  

This paper proposes a new approach to watermarking multimedia products based on the combination of redundant discrete wavelet transform and independent component analysis. The original image is decomposed by RDWT, and watermark is embedded in to LL sub-band frequency according mixing model of the ICA, after that for enhancing the robustness of the watermark, the perceptual model is applied via stochastic approach for watermark adapting. This is based on computation of a noise visibility function (NVF) which has local image properties so the strength of watermarking is controllable. Principal component analysis (PCA) whitening process and FastICA techniques are introduced to ensure a blind... 

Morphological filtering is a useful technique for the processing and analysis of binary and gray scale images. The extension of morphological techniques to color images is not a straightforward task because this extension stems from the multivariate ordering problem. Since multivariate ordering is ambiguous, existing approaches have used known vector ordering schemes for the color ordering purpose. In the. last decade, many different color morphological operators have been introduced in the literature. Some of them have focused on noise suppression purposes. However, none has shown good performance, especially on edgy regions. In this paper, new color morphological operators, based on a... 

A novel method is proposed in the scope of image segmentation that solves this problem by breaking it into two main blocks. The first block's functionality is a method to anticipate the color basis of each segment in segmented images. One of the challenges of image segmentation is the inappropriate distribution of colors in the RGB color space. To determine the color of each segment, after mapping the input image onto the HSI color space, the image colors are classified into some clusters by exploiting the K-Means. Then, the list of cluster centers is winnowed down to a short list of colors based on a set of criteria. The second block of the proposed method defines how each pixel of the... 

One of the most famous approaches for the segmentation of color images is finding clusters in the color space. Shapes of these clusters are often complex and the time complexity of the existing algorithms for finding clusters of different shapes is usually high. In this paper, a novel clustering algorithm is proposed and used for the image segmentation purpose. This algorithm distinguishes clusters of different shapes using a two-stage clustering approach in a reasonable time. In the first stage, the mean-shift clustering algorithm is used and the data points are grouped into some sub-clusters. In the second stage, connections between sub-clusters are established according to a dissimilarity... 

In this paper, we describe a real-time Gradient-based Multiple Faces Tracking (GMFT) algorithm in complex background. In GMFT method first faces are detected by combination of morphological facial feature extraction and gradient-based edge detection methods. After a face is reliably detected, it is tracked over time with a novel real-time algorithm. The algorithm has been implemented and tested under a wide range of real-world conditions. The resulting system runs in real-time on a standard PC, being robust to face scale variations, rotations in depth, and fast changes in subject/camera position. It has consistently provided performance which satisfies the following requirements: 1) able to... 

Skin detection is a difficult and primary task in many image processing applications. Because of the diversity of various image processing tasks, there exists no optimum method that can perform properly for all applications. In this paper, we have proposed a novel skin detection algorithm that combines color and texture information of skin with cellular learning automata to detect skin-like regions in color images. Skin color regions are first detected, by using a committee structure, from among several explicit boundary skin models. Detected skin-color regions are then fed to a texture analyzer which extracts texture features via their color statistical properties and maps them to a skin...