Multi-Directional Detection of Scratches in Digitized Images

Publication in the conference proceedings of EUSIPCO, Glasgow, Scotland, 2009

Copy-move Forgery Detection via Texture Description

Copy-move forgery is one of the most common type of tampering in digital images. Copy-moves are parts of the image that are copied and pasted onto another part of the same image. Detection methods in general use block-matching methods, which first divide the image into overlapping blocks and then extract features from each block, assuming similar blocks will yield similar features. In this paper we present a block-based approach which exploits texture as feature to be extracted from blocks. Our goal is to study if texture is well suited for the specific application, and to compare performance of several texture descriptors. Tests have been made on both uncompressed and JPEG compressed image…

Detecting multiple copies in tampered images

Copy-move forgeries are parts of the image that are duplicated elsewhere into the same image, often after being modified by geometrical transformations. In this paper we present a method to detect these image alterations, using a SIFT-based approach. First we describe a state of the art SIFT-point matching method, which inspired our algorithm, then we compare it with our SIFT-based approach, which consists of three parts: keypoint clustering, cluster matching, and texture analysis. The goal is to find copies of the same object, i.e. clusters of points, rather than points that match. Cluster matching proves to give better results than single point matching, since it returns a complete and co…

Combining Top-down and Bottom-up Visual Saliency for Firearms Localization

Object detection is one of the most challenging issues for computer vision researchers. The analysis of the human visual attention mechanisms can help automatic inspection systems, in order to discard useless information and improving performances and efficiency. In this paper we proposed our attention based method to estimate firearms position in images of people holding firearms. Both top-down and bottom-up mechanisms are involved in our system. The bottom-up analysis is based on a state-of-the-art approach. The top-down analysis is based on the construction of a probabilistic model of the firearms position with respect to the people’s face position. This model has been created by analyzi…

Content-Based Image Retrieval as Validation for Defect Detection in Old Photos

Depth-Aware Multi-object Tracking in Spherical Videos

This paper deals with the multi-object tracking (MOT) problem in videos acquired by 360-degree cameras. Targets are tracked by a frame-by-frame association strategy. At each frame, candidate targets are detected by a pre-trained state-of-the-art deep model. Associations to the targets known till the previous frame are found by solving a data association problem considering the locations of the targets in the scene. In case of a missing detection, a Kalman filter is used to track the target. Differently than works at the state-of-the-art, the proposed tracker considers the depth of the targets in the scene. The distance of the targets from the camera can be estimated by geometrical facts pec…

Texture Synthesis for Digital Restoration in the Bit-Plane Representation

In this paper we propose a new approach to handle the problem of restoration of grayscale textured images. The purpose is to recovery missing data of a damaged area. The key point is to decompose an image in its bit-planes, and to process bits rather than pixels. We propose two texture synthesis methods for restoration. The first one is a random generation process, based on the conditional probability of bits in the bit-planes. It is designed for images with stochastic textures. The second one is a best-matching method, running on each bit-plane, that is well suited to synthesize periodic patterns. Results are compared with a state-of-the-art restoration algorithm.

Copy–Move Forgery Detection by Matching Triangles of Keypoints

Copy-move forgery is one of the most common types of tampering for digital images. Detection methods generally use block-matching approaches, which first divide the image into overlapping blocks and then extract and compare features to find similar ones, or point-based approaches, in which relevant keypoints are extracted and matched to each other to find similar areas. In this paper, we present a very novel hybrid approach, which compares triangles rather than blocks, or single points. Interest points are extracted from the image, and objects are modeled as a set of connected triangles built onto these points. Triangles are matched according to their shapes (inner angles), their content (c…

Activity Monitoring Made Easier by Smart 360-degree Cameras

This paper proposes the use of smart 360-degree cameras for activity monitoring. By exploiting the geometric properties of these cameras and adopting off-the-shelf tracking algorithms adapted to equirectangular images, this paper shows how simple it becomes deploying a camera network, and detecting the presence of pedestrians in predefined regions of interest with minimal information on the camera, namely its height. The paper further shows that smart 360-degree cameras can enhance motion understanding in the environment and proposes a simple method to estimate the heatmap of the scene to highlight regions where pedestrians are more often present. Quantitative and qualitative results demons…

Automatic Generation of Custom Tourist Routes

In this paper we present a new tool for the automatic generation of custom tourist routes. Starting from the user preferences (place to visit, starting and ending points, available time, favourite types of attractions) our system is able to extract information from the Web and to suggest a custom route to the user. Our system is based only onto online information, which is dynamically extracted at the query time, so that it can work for every location in the world, with no restrictions. Furthermore, our method does not require any user intervention, unless the input parameters. Our system is also able to give to the users supplementary information about the route stops, as a photo slideshow…

A Set of Low-Level Descriptors for Images Affected by Foxing

Old printed photos are affected by several typical damages, due to age and bad preservation. “Foxing” defects look like red-brownish spots onto the paper of the printed photo. Similar features can be seen in the digitized copies. In this paper we propose a set of low level descriptors to extract features from digitized photos affected by foxing. An image retrieval application, based on information extracted by the proposed descriptors, is developed to discriminate, through comparison, if an image is affected by foxing. Results are compared to those obtained using some standard color descriptors.

Saliency Based Image Cropping

Image cropping is a technique that is used to select the most relevant areas of an image, discarding the useless ones. Handmade selection, especially in case of large photo collections, is a time consuming task. Automatic image cropping techniques may help users, suggesting to them which part of the image is the most relevant, according to specific criteria. We suppose that the most visually salient areas of a photo are also the most relevant ones to the users. In this paper we present an extended version of our previously proposed method, to extract the saliency map of an image, which is based on the analysis of the distribution of the interest points of the image. Three different interest…

A tool to support the creation of datasets of tampered videos

Digital Video Forensics is getting a growing interest from the Multimedia research community, as the need for methods to validate the authenticity of a video content is increasing with the number of videos freely available to the digital users. Unlike Digital Image Forensics, to our knowledge, there are not standard datasets to test video forgery detection techniques. In this paper we present a new tool to support the users in creating datasets of tampered videos. We furthermore present our own dataset and we discuss some remarks about how to create forgeries difficult to be detected by an observer, to the naked eye.

A knowledge based architecture for the virtual restoration of ancient photos

Abstract Historical images are essential documents of the recent past. Nevertheless, time and bad preservation corrupt their physical supports. Digitization can be the solution to extend their “lives”, and digital techniques can be used to recover lost information. This task is often difficult and time-consuming, if commercial restoration tools are used for the purpose. A new solution is proposed to help non-expert users in restoring their damaged photos. First, we defined a dual taxonomy for the defects in printed and digitized photos. We represented our restoration domain with an ontology and we created some rules to suggest actions to perform in case of some specific events. Classes and …

An Automated Visual Inspection System for the Classification of the Phases of Ti-6Al-4V Titanium Alloy

Metallography is the science of studying the physical properties of metal microstructures, by means of microscopes. While traditional approaches involve the direct observation of the acquired images by human experts, Com-puter Vision techniques may help experts in the analysis of the inspected mate-rials. In this paper we present an automated system to classify the phases of a Titanium alloy, Ti-6Al-4V. Our system has been tested to analyze the final products of a Friction Stir Welding process, to study the states of the micro-structures of the welded material.

Multidirectional Scratch Detection and Restoration in Digitized Old Images

Line scratches are common defects in old archived videos, but similar imperfections may occur in printed images, in most cases by reason of improper handling or inaccurate preservation of the support. Once an image is digitized, its defects become part of that image. Many state-of-the-art papers deal with long, thin, vertical lines in old movie frames, by exploiting both spatial and temporal information. In this paper we aim to face with a more challenging and general problem: the analysis of line scratches in still images, regardless of their orientation, color, and shape. We present a detection/restoration method to process this defect.

Visual saliency by keypoints distribution analysis

In this paper we introduce a new method for Visual Saliency detection. The goal of our method is to emphasize regions that show rare visual aspects in comparison with those showing frequent ones. We propose a bottom up approach that performs a new technique based on low level image features (texture) analysis. More precisely, we use SIFT Density Maps (SDM), to study the distribution of keypoints into the image with different scales of observation, and its relationship with real fixation points. The hypothesis is that the image regions that show a larger distance from the mode (most frequent value) of the keypoints distribution over all the image are the same that better capture our visual a…

Keyword Based Keyframe Extraction in Online Video Collections

Keyframe extraction methods aim to find in a video sequence the most significant frames, according to specific criteria. In this paper we propose a new method to search, in a video database, for frames that are related to a given keyword, and to extract the best ones, according to a proposed quality factor. We first exploit a speech to text algorithm to extract automatic captions from all the video in a specific domain database. Then we select only those sequences (clips), whose captions include a given keyword, thus discarding a lot of information that is useless for our purposes. Each retrieved clip is then divided into shots, using a video segmentation method, that is based on the SURF d…

A Dataset of Annotated Omnidirectional Videos for Distancing Applications

Omnidirectional (or 360°) cameras are acquisition devices that, in the next few years, could have a big impact on video surveillance applications, research, and industry, as they can record a spherical view of a whole environment from every perspective. This paper presents two new contributions to the research community: the CVIP360 dataset, an annotated dataset of 360° videos for distancing applications, and a new method to estimate the distances of objects in a scene from a single 360° image. The CVIP360 dataset includes 16 videos acquired outdoors and indoors, annotated by adding information about the pedestrians in the scene (bounding boxes) and the distances to the camera of some point…

Detection of Duplicated Regions in Tampered Digital Images by Bit-Plane Analysis

In this paper we present a new method for searching duplicated areas in a digital image. The goal is to detect if an image has been tampered by a copy-move process. Our method works within a convenient domain. The image to be analyzed is decomposed in its bit-plane representation. Then, for each bitplane, block of bits are encoded with an ASCII code, and a sequence of strings is analyzed rather than the original bit-plane. The sequence is lexicographically sorted and similar groups of bits are extracted as candidate areas, and passed to the following plane to be processed. Output of the last planes indicates if, and where, the image has been altered.

A Dual Taxonomy for Defects in Digitized Historical Photos

Old photos may be affected by several types of defects. Manual restorers use their own taxonomy to classify damages by which a photo is affected, in order to apply the proper restoration techniques for a specific defect. Once a photo is digitally acquired, defects become part of the image, and their aspect change. This paper wants to be a first attempt to correlate real defects of printed photos, and digital defects of their digitized versions. A dual taxonomy is proposed, for real and digital defects, and used to classify an image dataset, for a posteriori comparative study. Furthermore, a set of digital features is analyzed for digitized images, to identify which of them could be useful f…

Asymptomatic Carotid Lesions and Aging: Role of Hypertension and Other Traditional and Emerging Risk Factors

Background We evaluated the prevalence of intima-media thickening (IMT) and asymptomatic carotid plaque (ACP) in a group of subjects with or without traditional and/or emerging risk factors (RF). Methods There were 631 subjects (313 male and 318 female) aged between 19 and 97 years, asymptomatic for cerebro- and cardiovascular diseases. The following measurements were used: anamnesis, physical examination, height and sitting blood pressure. Biochemistry variables were also considered: total cholesterol, HDL-C, LDL-C, triglycerides, fibrinogen, high sensitive C-reactive protein, IgG antibodies for Helicobacter pylori (HP), cytotoxic HP, cytomegalovirus and Chlamydia pneumoniae . Finally, an …

Scale detection via keypoint density maps in regular or near-regular textures

In this paper we propose a new method to detect the global scale of images with regular, near regular, or homogenous textures. We define texture ''scale'' as the size of the basic elements (texels or textons) that most frequently occur into the image. We study the distribution of the interest points into the image, at different scale, by using our Keypoint Density Maps (KDMs) tool. A ''mode'' vector is built computing the most frequent values (modes) of the KDMs, at different scales. We observed that the mode vector is quasi linear with the scale. The mode vector is properly subsampled, depending on the scale of observation, and compared with a linear model. Texture scale is estimated as th…

Filling-in Gaps in Textured Images Using Bit-Plane Statistics

In this paper we propose a novel approach for the texture analysis-synthesis problem, with the purpose to restore missing zones in greyscale images. Bit-plane decomposition is used, and a dictionary is build with bit-blocks statistics for each plane. Gaps are reconstructed with a conditional stochastic process, to propagate texture global features into the damaged area, using information stored in the dictionary. Our restoration method is simple, easy and fast, with very good results for a large set of textured images. Results are compared with a state-of-the-art restoration algorithm.

Restoration of Digitized Damaged Photos using Bit-Plane Slicing

Digital image restoration aims to recover damaged zones of a digital image, using surrounding information. In this paper we propose a novel approach, based on bit-plane slicing decomposition, with the purpose to make information analysis and reconstruction process easy, fast and effective. Tests have been made on digitized damaged old photos to restore several classes of typical defects in old photographic prints.

Damages of Digitized Historical Images as Objects for Content Based Applications

This work presents the preliminary results achieved within a FIRB project aimed to develop innovative support tools for automatic or semi-automatic restoration of damaged digital images oncerning archaeological and monumental inheritance of Mediterranean coast. In particular, this paper is focused on a methodology for describing image degradation and its meta-representation for content based storing and retrieval. Our innovative idea is to decompose and store in a conventional RDBMS the images content, considering the damages as objects of the images. Moreover, a set of descriptors(a subset of MPEG7 descriptors) is used for the damage meta representation aimed to content based application. …

Automatic Illustration of Short Texts via Web Images

In this paper we propose a totally unsupervised and automatic illustration method, which aims to find onto the Web a set of images to illustrate the content of an input short text. The text is modelled as a semantic space and a set of relevant keywords is extracted. We compare and discuss different methods to create semantic representations by keyword extraction. Keywords are used to query Google Image Search engine for a list of relevant images. We also extract information from the Web pages that include the retrieved images, to create an Image Semantic Space, which is compared to the Text Semantic Space in order to rank the list of retrieved images. Tests showed that our method achieves v…

Toward an Integrated System for Surveillance and Behaviour Analysis of Groups and People

Security and INTelligence SYStem is an Italian research project which aims to create an integrated system for the analysis of multi-modal data sources (text, images, video, audio), to assist operators in homeland security applications. Within this project the Scientific Research Unit of the University of Palermo is responsible of the image and video analysis activity. The SRU of Palermo developed a web service based architecture that provides image and video analysis capabilities to the integrated analysis system. The developed architecture uses both state of the art techniques, adapted to cope with the particular problem at hand, and new algorithms to provide the following services: image …

State of the art in passive digital image forgery detection: copy-move image forgery

Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become easy as a result of powerful image processing software and human knowledge. The importance and relevance of digital image forensics has attracted various researchers to establish different techniques for detection in image forensics. The core category of image forensics is passive image forgery detection. One of the most important passive forgeries that affect the originality of the image is cop…

Extracting Touristic Information from Online Image Collections

In this paper, we present a Geographical Information Retrieval system, which aims to automatically extract and analyze touristic information from photos of online image collections (in our case of study Flickr). Our system collect all the photos, and the related information, that are associated to a specific city. We then use Google Maps service to geolocate the retrieved photos, and finally we analyze geo-referenced data to obtain our goals: 1) determining and locating the most interesting places of the city, i.e. the most visited locations, and 2) reconstructing touristic routes of the users visiting the city. Information is filtered by using a set of constraints, which we apply to select…

Scratches Removal in Digitised Aerial Photos Concerning Sicilian Territory

In this paper we propose a fast and effective method to detect and restore scratches in aerial photos from a photographic archive concerning Sicilian territory. Scratch removal is a typical problem for old movie films but similar defects can be seen in still images. Our solution is based on a semiautomatic detection process and an unsupervised restoration algorithm. Results are comparable with those obtained with commercial restoration tools.

I-MALL An Effective Framework for Personalized Visits. Improving the Customer Experience in Stores

In this paper we present I-MALL, an ICT hardware and software infrastructure that enables the management of services related to places such as shopping malls, showrooms, and conferences held in dedicated facilities. I-MALL offers a network of services that perform customer behavior analysis through computer vision and provide personalized recommendations made available on digital signage terminals. The user can also interact with a social robot. Recommendations are inferred on the basis of the profile of interests computed by the system analysing the history of the customer visit and his/her behavior including information from his/her appearance, the route taken inside the facility, as well…