Image Retrieval with Random Bubbles

In this work we propose an algorithm for content based im−age retrieval based on random selection of circular bubbles on the reference image. More specifically, an image finger−print vector is extracted from the image, the components of which are simple statistical parameters associated to the luminance values in some selected circular areas of the im−age. The positions and radius of these bubbles result from a random selection, with characteristics defined by the user. In this way, the extracted fingerprint is very robust with respect to linear and nonlinear distortion of the image. Experiments based on the detection of various linearly and nonlinearly distorted versions of a test image in a large database have shown very promising results

Even/odd decomposition made sparse: A fingerprint to hidden patterns

The very fundamental operation of even/odd decomposition is at the core of some of the simplest information representation and signal processing tasks. So far most of its use has been for rearranging data to provide fast implementations of various types of transforms (Fourier, DCT, …) or for achieving elementary data transformation, such as the Walsh–Hadamard transform. This work proposes to look into the decomposition framework to obtain a richer perspective. In the context of an iterated even/odd decomposition, it is possible to pinpoint intermediate layered levels of symmetries which cannot be easily captured in the original data. In addition this determines a hierarchical fingerprinting for any sort of continuous finite support analog signal or for any discrete-time sequence which may turn out useful in several recognition or categorization tasks. It also may help to achieve sparsity within a natural hierarchical framework, which could be easily extended for many other types of orthogonal transformations. This paper also suggests a global measure of the energy imbalance across the hierarchy of the decomposition to capture the overall fingerprinting of this interpretation

Representation of Signals by Local Symmetry Decomposition

In this paper we propose a segmentation of finite support sequences based on the even/odd decomposition of a signal. The objective is to find a more compact representation of information. To this aim, the paper starts to generalize the even/odd decomposition by concentrating the energy on either the even or the odd part by optimally placing the centre of symmetry. Local symmetry intervals are thus located. The sequence segmentation is further processed by applying an iterative growth on the candidate segments to remove any overlapping portions. Experimental results show that the set of segments can be more eficiently compressed with respect to the DCT transformation of the entire sequence, which corresponds to the near optimal KLT transform of the data chosen for the experiment

Image symmetries: The right balance between evenness and perception

A recent and fascinating interest in computational symmetry for computer vision and computer graphics applications has led to a remarkable realization of new symmetry detection algorithms. Such a concern is culminated in a symmetry detection competition as a workshop affiliated with the 2011 and 2013 CVPR Conferences. In this paper, we propose a method based on the computation of the symmetry level associated to each pixel. Such a value is determined through the energy balance of the even/odd decomposition of a patch with respect to a central axis (which is equivalent to estimate the middle point of a row-wise convolution). Peaks localization along the perpendicular direction of each angle allows to identify possible symmetry axes. The evaluation of a feature based on gradient information allows to establish a classification confidence for each detected axis. By adopting the aforementioned rigorous validation framework, the proposed method indicates significant performance increase

On reflection symmetry in natural images

Many new symmetry detection algorithms have been recently developed, thanks to an interest revival on computational symmetry for computer graphics and computer vision applications. Notably, in 2013 the IEEE CVPR Conference organized a dedicated workshop and an accompanying symmetry detection competition. In this paper we propose an approach for symmetric object detection that is based both on the computation of a symmetry measure for each pixel and on saliency. The symmetry value is obtained as the energy balance of the even-odd decomposition of a patch w.r.t. each possible axis. The candidate symmetry axes are then identified through the localization of peaks along the direction perpendicular to each considered axis orientation. These found candidate axes are finally evaluated through a confidence measure that also allow removing redundant detected symmetries. The obtained results within the framework adopted in the aforementioned competition show significant performance improvement

HDR Image Watermarking

In this Chapter we survey available solutions for HDR image watermarking. First, we briefly discuss watermarking in general terms, with particular emphasis on its requirements that primarily include security, robustness, imperceptibility, capacity and the availability of the original image during recovery. However, with respect to traditional image watermarking, HDR images possess a unique set of features such as an extended range of luminance values to work with and tone-mapping operators against whom it is essential to be robust. These clearly affect the HDR watermarking algorithms proposed in the literature, which we extensively review next, including a thorough analysis of the reported experimental results. As a working example, we also describe the HDR watermarking system that we recently proposed and that focuses on combining imperceptibility, security and robustness to TM operators at the expense of capacity. We conclude the chapter with a critical analysis of the current state and future directions of the watermarking applications in the HDR domain

Markov Chains Fusion for Video Scene Generation

In this paper we address the general issue of merging Markov chains used to model two instances of a given process with some properties in common. In particular, in this work we apply this scenario to a multimedia application that generates new video scenes mixing the original segments of a given movie. To perform the latter process, it is first necessary to describe the structure of the scenes in some way, which in our case is done through Markov chains. The video scenes are then recombined by fusing their corresponding models using the general method described here. We analyze and validate the proposed methodology only for this specific application, however the solution presented here could be used in a very diverse array of applications where Markov chains are routinely used, ranging from queuing modeling to financial decision processes

CBCD Based on Color Features and Landmark MDS-Assisted Distance Estimation

Content-Based Copy Detection (CBCD) of digital videos is an important research field that aims at the identification of modified copies of an original clip, e.g., on the Internet. In this application, the video content is uniquely identified by the content itself, by extracting some compact features that are robust to a certain set of video transformations. Given the huge amount of data present in online video databases, the computational complexity of the feature extraction and comparison is a very important issue. In this paper, a landmark based multi-dimensional scaling technique is proposed to speed up the detection procedure which is based on exhaustive search and the MPEG-7 Dominant Color Descriptor. The method is evaluated under the MPEG Video Signature Core Experiment conditions, and simulation results show impressive time savings at the cost of a slightly reduced detection performance

Control of mixing step in the bread production with weak wheat flour and sourdough

Recently, several old Italian grain varieties have been reinstated, and the market seems to reward the breads made with these flours. Among such varieties, cultivar Verna appears to be interesting because the regular consumption of bread obtained by this variety and sourdough provides beneficial effects on human health such as the improving of the lipid, inflammatory, and hemorheological profiles. However, flours derived from Verna shows low technological performances. For example, the W value of these flours, obtained with alveoghraphic tests and considered as the commercial standard for the flour “strength” evaluation, is largely inferior than the W values of the commercial flour blends currently used in the bread making process. Moreover, the W values broadly change among the batches of Verna flours, whereas, usually, commercial blends are provided to bakeries with standard technological properties. Hence, these properties of Verna flour could lead to developed or overworked doughs and therefore to breads of worse quality. In addition, the previous mentioned large variability of flours from Verna can affect also the sourdough microbiota. For these reasons the composition and activity of the sourdough microorganisms should be controlled while the mixing process should be able to adapt to the different flour properties. Some works, in literature, report that monitoring the electrical consumption could provide useful information about the dough rheology, and this could be used to monitor the mixing step. In the present work the effect of different mixing times are evaluated on breads made with Verna flour type 2 leavened with sourdough. Tests were carried out at industrial scale in two different days. During the tests the electric consumption was monitored to highlight some features suitable for the mixing phase control. The breads were evaluated in terms of loaf volume measurement, crumb image analysis and losses of moisture content during storage. The results show that the composition of the sourdough microbiota and the mixing time affects the produced bread, especially when it is baked with low technological performance flours. Bread baked with an appropriate mixing time shows higher loaf volumes and lower water losses during storage