nils-herrmann/clean_scirepeval huggingface dataset:
Video coding for wireless varying bit-rate communications based on area of interest and region representation

A coding method for videophone communications over wireless, varying bit-rate, channels, is proposed. This method is based on defining one or more areas of interest and breaking them into a number of arbitrarily shaped regions which are homogeneous in their motion. The interest areas in the current implementation are human faces. They are detected with the help of a 2D scene model which is a-priori constructed and is based on knowledge of the application context. A mixed intra/inter-frame coding method is used for the description of the shape and topology of the regions where each polygonal vertex is encoded in a costless manner, either with regards to its predecessor in the same frame, or to the corresponding vertex in the previous frame. This coding is based on rate/distortion optimization constrained by the instantaneously available bit-rate. The error coding is also performed in an adaptive prioritized manner and is restricted within the detected areas of interest.
A Convolutional Neural Network Approach for Objective Video Quality Assessment

This paper describes an application of neural networks in the field of objective measurement method designed to automatically assess the perceived quality of digital videos. This challenging issue aims to emulate human judgment and to replace very complex and time consuming subjective quality assessment. Several metrics have been proposed in literature to tackle this issue. They are based on a general framework that combines different stages, each of them addressing complex problems. The ambition of this paper is not to present a global perfect quality metric but rather to focus on an original way to use neural networks in such a framework in the context of reduced reference (RR) quality metric. Especially, we point out the interest of such a tool for combining features and pooling them in order to compute quality scores. The proposed approach solves some problems inherent to objective metrics that should predict subjective quality score obtained using the single stimulus continuous quality evaluation (SSCQE) method. This latter has been adopted by video quality expert group (VQEG) in its recently finalized reduced referenced and no reference (RRNR-TV) test plan. The originality of such approach compared to previous attempts to use neural networks for quality assessment, relies on the use of a convolutional neural network (CNN) that allows a continuous time scoring of the video. Objective features are extracted on a frame-by-frame basis on both the reference and the distorted sequences; they are derived from a perceptual-based representation and integrated along the temporal axis using a time-delay neural network (TDNN). Experiments conducted on different MPEG-2 videos, with bit rates ranging 2-6 Mb/s, show the effectiveness of the proposed approach to get a plausible model of temporal pooling from the human vision system (HVS) point of view. More specifically, a linear correlation criteria, between objective and subjective scoring, up to 0.92 has been obtained on a set of typical TV videos
Efficient Saliency-Based Repurposing Method

Images play a very relevant role in our daily life. People now can easily shoot and share pictures thanks to the exponential growth of the portable medias, such as digital cameras, mobile phone. As the display size of those devices is relatively small, browsing large pictures remains difficult. Content re-purposing is an elegant solution to deal with this problem. It consists in cropping the images in order to display only the most interesting parts of the picture. A new algorithm is proposed in this paper; the experiments described herein, leading to a qualitative and a quantitative assessment, show that the proposed solution outperforms the conventional method.
Considering Temporal Variations of Spatial Visual Distortions in Video Quality Assessment

The temporal distortions such as flickering, jerkiness, and mosquito noise play a fundamental part in video quality assessment. A temporal distortion is commonly defined as the temporal evolution, or fluctuation, of the spatial distortion on a particular area which corresponds to the image of a specific object in the scene. Perception of spatial distortions over time can be largely modified by their temporal changes, such as increase or decrease in the distortions, or as periodic changes in the distortions. In this paper, we have designed a perceptual full reference video quality assessment metric by focusing on the temporal evolutions of the spatial distortions. As the perception of the temporal distortions is closely linked to the visual attention mechanisms, we have chosen to first evaluate the temporal distortion at eye fixation level. In this short-term temporal pooling, the video sequence is divided into spatio-temporal segments in which the spatio-temporal distortions are evaluated, resulting in spatio-temporal distortion maps. Afterwards, the global quality score of the whole video sequence is obtained by the long-term temporal pooling in which the spatio-temporal maps are spatially and temporally pooled. Consistent improvement over objective existing video quality assessment methods is observed. Our validation has been realized with a dataset built from video sequences of various contents.
Markovian-based detection and extraction of defects on textured surfaces by spatio-temporal video processing

This paper proposes a method for the detection and extraction of poorly contrasted linear structures in textured flat areas. The method is a spatio-temporal processing based on an irregular Markov random field (MRF) modeling of the image plane. It combines in an appropriate way a pure intra-frame processing based on an irregular graph-based MRF modeling and a time recursive nonlinear filtering which provides the final topological structure of the defects. The application considered here is the detection and classification of various defects that may appear on a roadway, particularly cracks. The images are produced by a video camera on board a running vehicle and showing a perspective view of the pavement. The results produced by the spatio-temporal processing are significantly better than a purely spatial analysis method gives, as taking into account multiple views of the same section of a roadway allows one to increase a lot the ability to discriminate between distressed and fair textured pavements.
Decomposition and separated adaptive digital processing of degraded images with an visual quality criterion

In this paper, image restoration in the context of visual quality criterion and two-component image model is considered. Taking a signal as a two additive components is a very useful way for modeling the two fundamental features of images : edges and textures. We propose a new algorithm which splits the luminance signal of complex images into plateau luminance signal and texture. The method is based on 2-D median filtering with adaptive support shape and offset as estimator of the local-luminance mean value. Using an objective visual quality criterion deduced from a model of human perception, separate adaptive 2-D linear filtering are performed on the two components according to specific action the degradations have made on.
Image segmentation by region-contour cooperation for image coding

Describes a method of image segmentation for image coding based on contour detection and region-growing procedures. Contour detection allows one to find the most evident frontiers of homogeneous regions. The region-growing procedure serves to close contours and to obtain more precise segmentation. The original idea of the method is the choice of growing centres which are placed on the skeleton of non-closed regions and used in split-and-merge procedure of region growing. The method allows one to obtain staircase closure of original contours which is easy to code.<<ETX>>
A spatio-temporal model of the selective human visual attention

A new spatio-temporal model for simulating the bottom-up visual attention is proposed. It has been built from numerous important properties of the human visual system (HVS). This paper focuses both on the architecture of the model and on its performances. Given that the spatial model of the bottom-up visual attention has already been defined [O. Le Meur et al., 2004], the temporal dimension is more accurately described. A qualitative and quantitative comparison with human fixations collected from an eye tracking apparatus is undertaken. From the former, the quality of the prediction is deemed very good whereas the latter illustrates that the best predictor of the human fixation consists of the sum all visual features (achromatic, chromatic and motion).
Segmentation of complex documents multilevel images: a robust and fast text bodies-headers detection and extraction scheme

We present a method for segmenting multilevels images of documents. The documents are considered difficult ones in the sense they may contain text paragraphs with different orientations and shapes, mixed with graphics and photographs. The proposed method extracts and separates blocks of text lines (printed or handwritten characters) and headers as well as stroke structures. The generic approach is first based on a multiscale analysis with the use of a pyramid representation of the image. At each level, text location is performed by a line borders detection scheme. Then, an efficient bottom-up procedure generates bodies (text paragraphs) as the output of algebric transformations upon a set of four directed graphs associated with the topological relationships of physical components.
Spatio-temporal segmentation and regions tracking of high definition video sequences based on a Markov Random Field model

In this paper, we propose a Markov random field sequence segmentation and regions tracking model, which aims at combining color, texture, and motion features. First a motion-based segmentation is realized. Namely the global motion of the video sequence is estimated and compensated. From the remaining motion information, a rough motion segmentation is achieved. Then, we use a Markovian approach to update and track over time the video objects. The spatio-temporal map is updated and compensated using our Markov Random Field segmentation model to keep consistency in video objects tracking.
A bar code location algorithm using a two-dimensional approach

Proposes a method for locating bar code blocks on parcels. One of the main difficulties involved is the combination of the very poor quality and the potential high complexity of the gray-level images. The image resolution has been chosen to be as low as possible in order to enlarge the field of view for a given number of CCD elements. Furthermore the focus of the camera has previously needed to be kept constant in spite of the variation in height of the objects resulting in the presence of high convolution distortion such that the width of the point spread function can be much larger than the width of a single stripe. The approach relies on the extraction of areas having a high density of mono-oriented gradient. This bar code finder algorithm works correctly for all images of a base provided by the French postal services.<<ETX>>
A Markov random field for rectilinear structure extraction in pavement distress image analysis

This paper deals with the detection and extraction of poorly contrasted rectilinear structures in textured areas, using a Markov random field model. The application is in the analysis of pavement distress, and more particularly pavement cracks. A local crack detection is first performed, where the pavement texture is seen as additive correlated noise. The resulting line image is then projected onto a regular lattice composed of straight line segments. A graph structure is associated with this lattice, which allows the definition of a Markovian crack model, where sites are no longer the image pixels, but straight line segments. The model is used to determine the location and shape of the rectilinear structures, with a given orientation, in the observed lattice. The actual defects can then be extracted by simple post-processing.
Binkey: a system for video content analysis "on the fly"

A system for automatic and fast structuring of video sequences allowing detection of shot changes, dominant motion estimation, and extraction of areas of interest is proposed. It is based on the analysis of a 1-D representation of video frames by a Mojette transform, a discrete version of the Radon transform. Motion is estimated by analysis of the projected motion in the transform domain. The proposed method uses statistical techniques based on cross-correlation measurement and outliers rejection which ensure its general robustness, specifically in the case of mobile objects. Results of this computation are then used for the detection of shot change and for the localization of areas of interest in the image plane. The analysis of a 1-D representation of video frames rather than the usual 2-D image reduces the complexity by itself and gives the possibility of video partitioning and object extraction "on the fly".
An image quality assessment method based on perception of structural information

This paper presents a new method to evaluate the quality if distorted images. This method is based on a comparison between the structural information extracted from the distorted image and from the original image. The interest of our method is that it uses reduced references containing perceptual structural information. First, a quick overview of image quality evaluation methods is given. Then the implementation of our human visual system (HVS) model is detailed. At last, results are given for quality evaluation of JPEG and JPEG2000 coded images. They show that our method provides results which are highly correlated with human judgments (mean opinion score). This method has been implemented in an application available on the Internet.
Classification Of The Chromosomes With Density Profile

Human chromosomes (22 pairs + 2 sex chromosomes) can be classified into 7 groups (Denver's yups) according to their lengths and centromere indexes [21]. he can be classified into their individual classes with the adied banding pattern information. The band chain in a chromosome is usually represented by a 1-D curve, so called densit profile. In this paper, the existing techniques using profile fyor the automatic chromosome classification are reviewed and compared on the same data-base. Some new lobal features are presented and a new local description methos, which is based on the statistics of the band appearance frequency of the R-banded chromosome, is also presented.
Extraction of the relative depth information of objects in video sequences

The paper presents a method for an automatic extraction of relative depth of objects in monocular video sequences. Video sequences are represented as a 2D and 1/2 combination of plane objects corresponding to video object plans (MPEG4) with associated affine motion. The method is based on the the analysis of integral profile of the grey-level function of objects which is computed by a discrete version of Radon transform.
Grouping video shots into scenes based on 1D mosaic descriptors

This paper describes an original approach for structuring video documents into scenes by grouping video shots. The method is based on the construction of 1D mosaics. 1D mosaics are built based on X-ray projections of color video frames representing integration along vertical and horizontal axes. The mosaicing is realized by motion compensation in a 1D domain. Grouping of shots in a scene is done by local and global matching of mosaics, based on piecewise linear approximation and hierarchical clustering. The results obtained on feature documentaries are promising.
Image coding in the context of a psychovisual image representation with vector quantization

The two main functions, decomposition and quantization, of the coding scheme described are entirely based on psychovisual aspects. From psychophysical experiments, the peripheral parts of the human visual system have been modeled by a set of nineteen channels and a nondirectional low residue. To perform this decomposition, filters similar to the cortex filters have been designed and used. The quantizers have been designed for each of the visual subband by evaluating the perception of quantization impairments on natural images. The images have been characterized by the local bandlimited contrast. It has been shown that these images must always be uniformly quantized in order to achieve a just noticeable quantization noise. The performance of the coding scheme based on the results above have been evaluated in terms of the peak signal to noise ratio, entropy and visual quality. The results show that at medium and low signal to noise ratios the visual quality of the reconstructed image remains much better than for "classical" schemes.
Tracking of hierarchical active meshes for object based manipulation of video content

This paper proposes a method for an accurate tracking of objects contained in video sequences thus allowing access and manipulation of video objects along the time. Each video object is represented both by a triangulated mesh and a polygonal mesh. The polygonal mesh results from a bottom up motion-based segmentation of a video sequence. This model is hierarchical: a video object plane (VOP) is the top of a segmentation pyramid. Each level in it is characterized by its proper quality of motion compensation. The triangulated mesh is a union of Delaunay meshes on each polygonal region of the VOP. Tracking is realized both on polygonal and triangulated meshes.
Which semi-local visual masking model forwavelet based image quality metric?

Properties and models of the human visual system (HVS) are the fundaments for most of sufficient objective image or video quality metrics. Among HVS properties, visual masking is a sensitive issue. Many models exist in literature. Simplest models can only predict visibility threshold for very simple cue while for natural images one should consider more complex approaches such as semi-local masking. Our previous work has shown the positive impact of incorporating semi-local masking in image quality metric according to one subjective study. It is important to consolidate this work with different subjective experiments. In this paper, different visual masking models, including contrast masking and semi-local masking, are evaluated according to three subjective studies. These subjective experiments were conducted with different protocols, different types of display devices, different contents and different populations.
A fast multiresolution text line and non text-line structures extraction and discrimination scheme for document image analysis

This work is devoted to the description and the evaluation of a generic method for locating text and lines in document images. One of the possible applications of this scheme is to detect and carefully extract the destination address block (DAB) on flat mail pieces. Concerning the low level design stages, the methodology is based on a multiresolution description of the document image and a joint extraction of both text lines and non text lines using their global aspect. Intermediate and high level stages consist of grouping text words into block structures, and this is performed in a efficient and robust way relying not only on some lines properties, but also on the adjacent lines.<<ETX>>
Application of a hybrid neural network for the discrimination of seeds by artificial vision

Intelligent hybrid systems are playing an increasing role in the development of artificial intelligence. In this study, we applied simulated annealing to adjust the weights of a multilayer neural network (MNN). Two versions of simulated annealing were tested: conventional simulated annealing (CSA) and fast simulated annealing (FSA). The applied hybrid system was used as a classifier in order to discriminate between 3 seed species (1 cultivated seed species which is perennial rye grass, and 2 adventitious seed species which are rumex and wild oat). From a set of colour digital images, 73 morphometrical and textural features were extracted to characterise each individual seed. Stepwise discriminant analysis made it possible to select the first 3 relevant features. The performances of classification were highly dependent on the scaling parameters of simulated annealing. For example, when the number of iterations of simulated annealing was 5, and the number of temperatures was 40, the combination between CSA and MNN correctly classified 98.18 and 97.77 percent of the training and the test sets, whereas FSA and MNN identified 99.18 and 99.68 percent of the same data sets. Globally, FSA outperformed CSA both in reliability and computational resources. A hybrid system combined with a colour image analysis showed promise for the design of an automatic seed identification device.
Coding of structure in the region-based coder as a problem of optimization on graphs

This paper deals with the coding of structure in region-based coders for moving sequences of images. The sequence of images is represented as spatio-temporal map of regions homogeneous regarded to motion-based criterion and characterized by their shape model, topological relations and motion parameters. Topological and geometrical models of spatio-temporal segmentation are introduced. The coding of geometrical information is formulated as the problem of the construction of the Eulerian circuit in planar non-connected graph. A suboptimal algorithm is proposed. Some results for teleconference sequence are given.
Optimization of a monochrome picture coding scheme based on a two-component model

The optimization of a monochrome still picture coding system is discussed. The coding scheme is based on a two-component model: a structural one (plateau component) and a texture component. The coding uses first a segmentation process based on edge-detection and contour-following technique, which produces connected and closed homogeneous regions. The picture associated with the plateau component is optimally coded and decoded by special techniques used in image synthesis. The texture component is optimally coded by an adaptive discrete cosine transform coding scheme after some specific preprocessing. The desired compression ratio is high (<1 bit/pel on a typical TV scene) while conserving an excellent visual quality.<<ETX>>
Visual features for image quality assessment with reduced reference

This paper focuses on the definition and selection of features to design a reduced description image quality assessment method. For such methods, the main problem is the choice of the features which constitute this reduced description. The best features are the ones which enable to produce the highest correlation between produced quality scores and subjective ones. So we test several feature types and measure their impact for image quality assessment. We show that the use of structural information and the combination of different feature types permit to get high performances.
A robust and multiscale document image segmentation for block line/text line structures extraction

This paper presents a new approach dealing with the extraction of blocks of lines and with discrimination between the text line and nontext lines structures. This approach combines a multiresolution textural description of the document image with a cooperation between adjacent resolution levels. At the same time, a not purely bottom-up structural procedure allows us to construct in a very robust way text lines and nontext lines structures and group them into fairly homogeneous blocks. The efficiency of the overall method is demonstrated by its ability to segment and extract destination address block (DAB) on quite diverse and complex images of flat mail pieces.