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This is happening : #life through the lens of Instagram
\"Featuring nearly 200 photos, [this collection] is the first-ever crowd-sourced book of images shot by and for Instagram users. This is a slice of life seen through the moments that give us pause, make us smile, and fill us with wonder\"--Page 2 of cover.
Book
Visual Cryptography and Secret Image Sharing
This book covers an extensive range of topics related to visual cryptography techniques and secure image sharing solutions. It addresses sharing multiple secrets and visual cryptography schemes based on the probabilistic reconstruction of the secret image, including pictures in the distributed shares, contrast enhancement techniques, visual cryptography schemes based on different logical operations for combining shared images, cheating prevention, and the alignment problem for image shares. The book also describes practical applications, steganography, and authentication. Case studies demonstrate the effectiveness of the techniques.
eBook
Read this if you want to be Instagram famous
Packed with the essential secrets of the hottest Instagrammers around, all you have to do is put their advice into practice. With tips covering photographic techniques, captioning, codes of conduct, kit and managing your account, soon you too will be hailed as a Instragram icon!!!
Book
Dual-Personality DICOM-TIFF for Whole Slide Images: A Migration Technique for Legacy Software
Despite recently organized Digital Imaging and Communications in Medicine (DICOM) testing and demonstration events involving numerous participating vendors, it is still the case that scanner manufacturers, software developers, and users continue to depend on proprietary file formats rather than adopting the standard DICOM whole slide microscopic image object. Many proprietary formats are Tag Image File Format (TIFF) based, and existing applications and libraries can read tiled TIFF files. The sluggish adoption of DICOM for whole slide image encoding can be temporarily mitigated by the use of dual-personality DICOM-TIFF files. These are compatible with the installed base of TIFF-based software, as well as newer DICOM-based software. The DICOM file format was deliberately designed to support this dual-personality capability for such transitional situations, although it is rarely used. Furthermore, existing TIFF files can be converted into dual-personality DICOM-TIFF without changing the pixel data. This paper demonstrates the feasibility of extending the dual-personality concept to multiframe-tiled pyramidal whole slide images and explores the issues encountered. Open source code and sample converted images are provided for testing.
Journal Article
Instagramھ : how Kevin Systrom & Mike Krieger changed the way we take and share photos
With a popular website and smartphone app, Instagram has become one of the best ways to share pictures with friends. Instagram, however, was once just the idea of two men: Kevin Systrom and Mike Krieger. Together, these two men have taken Instagram to new heights and made it one of the most popular tech companies. Discover their story. Find out how Instagram grew to what it is today.
Book
IPAC Image Processing and Data Archiving for the Palomar Transient Factory
The Palomar Transient Factory (PTF) is a multiepochal robotic survey of the northern sky that acquires data for the scientific study of transient and variable astrophysical phenomena. The camera and telescope provide for wide-field imaging in optical bands. In the five years of operation since first light on 2008 December 13, images taken with Mould-R and SDSS-g′ camera filters have been routinely acquired on a nightly basis (weather permitting), and two different Hα filters were installed in 2011 May (656 and 663 nm). The PTF image-processing and data-archival program at the Infrared Processing and Analysis Center (IPAC) is tailored to receive and reduce the data, and, from it, generate and preserve astrometrically and photometrically calibrated images, extracted source catalogs, and co-added reference images. Relational databases have been deployed to track these products in operations and the data archive. The fully automated system has benefited by lessons learned from past IPAC projects and comprises advantageous features that are potentially incorporable into other ground-based observatories. Both off-the-shelf and in-house software have been utilized for economy and rapid development. The PTF data archive is curated by the NASA/IPAC Infrared Science Archive (IRSA). A state-of-the-art custom Web interface has been deployed for downloading the raw images, processed images, and source catalogs from IRSA. Access to PTF data products is currently limited to an initial public data release (M81, M44, M42, SDSS Stripe 82, and the Kepler Survey Field). It is the intent of the PTF collaboration to release the full PTF data archive when sufficient funding becomes available.
Journal Article
Handbook of image-based security techniques
This book focuses on image based security techniques, namely visual cryptography, watermarking, and steganography. The first section explores basic to advanced concepts of visual cryptography (VC). The second section covers Digital Image Watermarking including watermarking algorithms, frameworks for modeling watermarking systems, and the evaluation of watermarking techniques. The final section analyzes Steganography, including the notion, terminology and building blocks of steganographic communication. The book includes many examples and applications, as well as implementation using MATLAB-- Provided by publisher.
Book
ODRP: a new approach for spatial street sign detection from EXIF using deep learning-based object detection, distance estimation, rotation and projection system
Geographical information systems (GIS) are the systems where spatial data are stored and analyzed. The most important raw material in GIS is spatial data. Thus, it is essential to collect and update these data. On the other hand, exchangeable image file (EXIF) format is a special file format that contains camera direction, date-time information and GPS location provided by a digital camera that captures the images. Transferring the objects in EXIF data sets with absolute coordinates on the earth significantly contributes to GIS. In this study, a new hybrid approach, ODPR, which utilizes object detection (O), distance estimation (D), rotation (R) and projection (P) methods, is proposed to detect street sign objects in EXIF with their locations. The performance of the proposed approach has been examined on the natural EXIF data sets obtained from the Kayseri Metropolitan Municipality. In the proposed approach, a deep learning method detects a street sign object in the EXIF. Then, the object’s distance is calculated at the point where the photograph is taken. Finally, the spatial location of the detected object on the earth is calculated using distance, direction and GPS data with rotation and projection methods. In the proposed ODRP approach, the performances of convolutional neural network (CNN)-based Faster R-CNN, YOLO V5, YOLO V6 and transformer-based DETR models as deep learning models for object detection are examined. The F1 score metric is widely used to examine the performance of methods in deep learning models. The performances of the proposed approaches are reviewed according to the F1 score values, and ODRP Faster R-CNN, YOLO V5, YOLO V6 and DETR approaches achieved F1 scores of 0.909, 0.956, 0.948 and 0.922, respectively. In addition, to overcome the variability of light and background mixing problems, an improved supervised learning method (ISL) is proposed. Thanks to ISL, ODRP Faster R-CNN, YOLO V5, YOLO V6, and DETR approaches have reached 0.965, 0.985, 0.969 and 0.942 f1 scores, respectively. The proposed ODRP Faster R-CNN, YOLO V5, YOLO V6 and DETR approaches found the location of the street sign object to be 11434.76, 12818.39, 12454.63 and 9843.57 ms closer to its position on earth than the classical method, which considers the location of the EXIF, respectively. Regarding time cost, the ODRP Faster R-CNN, YOLO V5, YOLO V6 and DETR analyze EXIF data at an average of 0.99, 0.42, 0.41 and 0.53 s, respectively. The run time of the ODRP YOLO V5 and V6 approaches is almost equal to each other, and it works approximately 2.5 times faster than the ODRP Faster R-CNN method. Consequently, ODRP YOLO V5 outperforms ODRP Faster R-CNN, YOLO V6 and DETR for detecting the spatial location of street sign objects in EXIF and the F1 score.
Journal Article
ITC-MNP: a diverse dataset for image file fragment classification
Objectives
Image file fragment classification is a critical area of study in digital forensics. However, many publicly available datasets in this field are derived from a single source, often lacking consideration of the diversity in image settings and content. To demonstrate the effectiveness of a given methodology, it is essential to evaluate it using datasets that are sampled from varied data sources. Therefore, providing a sufficiently diverse dataset is crucial to enable a realistic assessment of any proposed method.
Data description
The dataset includes image file fragments of 4096 bytes from five formats (JPG, BMP, GIF, PNG, and TIFF), each processed with different conversion settings. The source images are categorized into three content types: Nature, People, and Medical. In total, the dataset contains 501,000 fragments. These fragments consist of file headers and incomplete end-of-file fragments, completed with random bytes to approximate how operating systems handle data when file sizes are not multiples of the sector size. This approach aims to simulate typical scenarios where fragments are recovered from a hard drive, though it may not capture all real-world complexities such as data corruption and complex file structures.
Journal Article
Portable Moving Images
This media history explores a series of portable small cameras, playback devices, and storage units that have made the production of film and video available to everyone. Covering several storage formats from 8mm films of the 1900s, through the analogue videotapes of the 1970s, to the compression algorithms of the 2000s, this work examines the effects that the shrinkage of complex machines, media formats, and processing operations has had on the dissemination of moving images. Using an archaeological approach to technical standards of media, the author provides a genealogy of portable storage formats for film, analog video, and digitally encoded video. This book is a step forward in decoding the storage media formats, which up to now have been the domain of highly specialised technicians.
eBook