MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

Color image segmentation: advances and prospects

One of the challenging issues for Orthogonal Frequency Division Multiplexing (OFDM) system is its high Peak-to-Average Power Ratio (PAPR). In this paper, we review and analysis different OFDM PAPR reduction techniques, based on computational complexity, bandwidth expansion, spectral spillage and performance. We also discuss some methods of PAPR reduction for multiuser OFDM broadband communication systems.

https://engold.ui.ac.ir/~sabahi/Advanced%20digital%20communication/An%20Overview%20Peak-to-Average%20Power%20Ratio%20Reduction%20Reduction%20Techniques%20for%20OFDM%20Signals.pdf

An Overview: Peak-to-Average Power Ratio Reduction Techniques for OFDM Signals

Computer and Robot Vision Vol. 1, by R.M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10887-1.

Computer and Robot Vision

This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

A reflectance model for computer graphics

This paper presents an orthogonal frequency division multiplexing (OFDM) system, which through the use of sub-optimal PTS combined with a preset threshold, achieves low computational complexity to find optimum weighting factors. A specific bit in weighting factor that leads to a smaller peak-to-average power ratio (PAP) is identified from the sub-optimum method. And a specific threshold, which found from the OFDM frame probability, is also applied to reduce computational complexity. The performance of the proposed method was slightly degraded compared to that of optimum method, PTS. However, the complexity of the proposed method was remarkably lower than that of the optimum method.

Multi-carrier PAP reduction method using sub-optimal PTS with threshold

An important problem in color-based image retrieval and video segmentation is to lack information about how color is spatially distributed. To solve this problem and enhance the performance of image and video analyses, a spatial color descriptor is proposed involving a color adjacency histogram and color vector angle histogram. The color adjacency histogram represents the spatial distribution of color pairs at color edges in an image, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, the color vector angle histogram represents the global color distribution of smooth pixels in an image. Since the proposed color descriptor includes spatial adjacency information between colors, it can robustly reduce the effect of a significant change in appearance and shape in image and video analyses. Moreover, since the color adjacency histogram is simply represented by binary streams, the storage space required for the image histogram values can be effectively reduced. Experimental results show that even with significant appearance changes, the proposed color descriptor could produce a high image retrieval rate and accurately detect abrupt scene-cuts in a video analysis.

Spatial color descriptor for image retrieval and video segmentation

Current NTSC systems employ an interlaced scan scheme where visually annoying artifacts, such as line flickers, large area flickers, and edge flickers, are inevitably generated and more objectionable with a larger display. With the development of HDTV systems, how an NTSC signal can be displayed in an HDTV system has also become a problem. Accordingly in order to solve these problems, many adaptive scan rate up-conversion systems have been proposed. The proposed system consists of a modified edge directional line averaging (ELA) interpolation module and contrast enhancement module. The modified ELA interpolation module reduces the visually annoying artifacts induced by an interlaced scan scheme whereas the degradation in the contrast and details due to interpolation processing is compensated by the contrast enhancement module. Moreover, the proposed system is easy to implement and the VLSI architecture is very simple. This new system was mainly developed for doubling the scan rate in an NTSC system; however, it can also be used in the format conversion in an HDTV system.

Yeong-Ho Ha

Papers

Multi-carrier PAP reduction method using sub-optimal PTS with threshold

Spatial color descriptor for image retrieval and video segmentation

Adaptive scan rate up-conversion system based on human visual characteristics

Stereo matching using genetic algorithm with adaptive chromosomes

Stereo correspondence using the Hopfield neural network of a new energy function