In this paper, we present a new tool for forensic recovery of single and multi-fragment JPEG/JFIF data files. First, we discuss the basic design and the technical methods composing our proposed data carving algorithm. Next, we compare the performance of our method with the well-known Adroit Photo Forensics (APF) state-of-the art tool. This comparison is centered on both the carving results as well as the obtained data processing speed, and is evaluated in terms of the results that can be obtained for several well-known reference data sets. Important to note is that we specifically focus on the fundamental recovery and fragment matching performance of the tools by forcing them to use various assumed cluster sizes. We show that on all accounts our new tool can significantly outperform APF. This improvement in data processing speed and carving results can be mostly attributed to novel methods to iterate and reduce the data search space and to a novel parameterless method to determine the end of a fragment based on the pixel data. Finally, we discuss several options for future research.

Manual reconstruction of ripped-up documents can be a very difficult and time-consuming task. This paper discusses a semi-automatic toolset that can be used for reconstructing ripped-up documents. First, we present a brief overview of our current fragment scanning,image segmentation and feature computation methods. Then, we discuss how fragments can be matched using their computed features. Next, we report on our global multi-fragment matching strategy and discuss the interactive components of the toolset that can be used to control and iterate through an entire reconstruction process. Finally, we illustrate the efficiency of the proposed approach with experimental results.

In this paper we present a method for interpolating images that also preserves sharp edge information. We concentrate on tackling blurred edges by mapping level curves of the image. Level curves or isophotes are spatial curves with constant intensity. The mapping of these intensities can be seen as a local contrast enhancement problem, therefore we can use contrast enhancement techniques coupled with additional constraints for the interpolation problem. A great advantage of this approach is that the shape of the level set contours is preserved and no explicit edge detection is needed here. Results show an improvement in visual quality: edges are sharper and ringing effects are removed.

In this paper we point out that the general principle "do not compute what you do not need to compute" can be applied easily and successfully within a MPEG audio decoding strategy. More specifically, we will discuss the problem of eliminating costly computation cycles being wasted at processing useless zero-valued data. Hence, the title: "do not zero-pute". At first, this may all sound somewhat obvious or trivial. Indeed, this can be true in many cases, but experience gathered in various teaching related projects during several academic years has also lead us to believe the opposite. Moreover, a survey of the existing literature quickly reveals that the approach discussed below has not been investigated and documented properly. Although we will only illustrate our optimization approach by discussing the MPEG-audio layer II decoding process in detail, we hope the reader will be able to apply, extend, and implement the basic principles presented here within many other applications.

The aim of this paper is to present a methodology to generate a partition of an image and a hierarchical region merging scheme to improve the meaningfulness of the segmentation, by reducing excessive object fragmentation. The segmentation method is based on the watershed transform applied to the image gradient magnitude. Prior to the actual segmentation, the image is smoothed to decrease the amount of detail detected by the watershed transform. To further improve the segmentation result, we use an iterative region merging process that uses a graph to represent the image partitions. In this process the most similar pair of adjacent regions is sequentially merged according to a predefined similarity metric. We investigate the use of a combined region merging criterion that takes into account both the intensity similarity and the contrast at the boundary of two adjacent regions. Results obtained illustrate the good combined performance of this segmentation and merging methods and the usefulness of the combined similarity function.

In this letter, we discuss a recursive optimization approach for the subband synthesis windowing component used in all three layers of the MPEG-1 and -2 audio decoding frameworks. We explain the design of the proposed algorithm and briefly discuss how it can be combined with other novel and existing optimization strategies. The impact of these optimizations on the number of multiplications and additions is shown, and the influence of the algorithm on the amount of memory required by the adapted decoder is also discussed. We show that the proposed algorithm offers very interesting possibilities for implementing efficient VLSI designs.

This paper discusses a recursive optimization approach for the subband synthesis windowing component used in all three layers of the MPEG-1 and −2 audio decoding standards. First, we explain the design of the proposed algorithm and illustrate how it can be combined with other optimization strategies that have already been discussed in the literature. Next, we discuss how the recursive optimizations reduce the required number of multiplications which often restrict the possibilities for implementing efficient hardware designs. Finally, we summarize the influence of the algorithm on the amount of memory required by the decoder.

We investigate a special-purpose application of MPEG-1 layer II audio streaming. First, we discuss how two or more already coded MPEG-audio bitstreams can be manipulated and mixed within the coded subband domain by using an appropriate algorithm for combining and recalculating the bit allocation. Next, we show that very significant speedups can be obtained compared with mixing in the temporal domain. We also illustrate that, at the same time, the system can act as a bit rate scaling device, using one of the bit allocation-combination algorithms which we implemented. The results obtained with these different algorithms are discussed and compared. Finally, we report on how the developed software was integrated into an Internet audio streaming system, which is now able to allow simple, yet efficient, real-time mixing of several MPEG-audio coded signals.

We present a method to detect roads and building boundaries on high resolution aerial photographs. These image features are found through the use of a line detection algorithm that is based on the three following steps: first, pre-smoothing, to remove noise and possibly irrelevant small scale details; this is followed by an automatic threshold of the gradient magnitude, thus generating a binary edge map; and in order to detect straight lines, this edge map is then used as the input of the Hough transform. We describe these steps with particular emphasis on the gradient threshold and show typical results obtainable with this method.

We assess the performance of a thresholded merging technique used as part of a procedure to obtain a motion-based segmentation of an image sequence. First an initial estimate for the motion field is obtained by using an improved block matching method. Then, an intensity-based initial segmentation is performed, using watershed segmentation on a non-linearly diffused version of the image. Next, a motion vector based on the initial motion field is calculated for each segment, and, finally, the obtained segments and their motion vectors are fed into the motion-based merging scheme, yielding the final segmentation. Results for a thresholded minimum distance merging technique are given and are compared with a K-means clustering algorithm.