Identifying person re-occurrences for personal photo management applications

Automatic identification of "who" is present in individual digital images within a photo management system using only content-based analysis is an extremely difficult problem. The authors present a system which enables identification of person reoccurrences within a personal photo management application by combining image content-based analysis tools with context data from image capture. This combined system employs automatic face detection and body-patch matching techniques, which collectively facilitate identifying person re-occurrences within images grouped into events based on context data. The authors introduce a face detection approach combining a histogram-based skin detection model and a modified BDF face detection method to detect multiple frontal faces in colour images. Corresponding body patches are then automatically segmented relative to the size, location and orientation of the detected faces in the image. The authors investigate the suitability of using different colour descriptors, including MPEG-7 colour descriptors, color coherent vectors (CCV) and color correlograms for effective body-patch matching. The system has been successfully integrated into the MediAssist platform, a prototype Web-based system for personal photo management, and runs on over 13000 personal photos

Source identification for mobile devices, based on wavelet transforms combined with sensor imperfections

One of the most relevant applications of digital image forensics is to accurately identify the device used for taking a given set of images, a problem called source identification. This paper studies recent developments in the field and proposes the mixture of two techniques (Sensor Imperfections and Wavelet Transforms) to get better source identification of images generated with mobile devices. Our results show that Sensor Imperfections and Wavelet Transforms can jointly serve as good forensic features to help trace the source camera of images produced by mobile phones. Furthermore, the model proposed here can also determine with high precision both the brand and model of the device

Using image-based modelling (SfM-MVS) to produce a 1935 ortho-mosaic of the Ethiopian highlands

Approximately 34,000 aerial photographs covering large parts of Ethiopia and dating back to 1935-1941 have been recently recovered. These allow investigating environmental dynamics for a past period that until now is only accessible from terrestrial photographs or narratives. As the archive consists of both oblique and vertical aerial photographs that cover rather small areas, methods of image-based modelling were used to orthorectify the images. In this study, 9 vertical and 18 low oblique aerial photographs were processed as an ortho-mosaic, covering an area of 25 km(2), west of Wukro town in northern Ethiopia. Using 15 control points (derived from Google Earth), a Root Means Square Error of 28.5 m in X 35.4 m in Y were achieved. These values can be viewed as optimal, given the relatively low resolution and poor quality of the imagery, the lack of metadata, the geometric quality of the Google Earth imagery and the recording characteristics. Land use remained largely similar since 1936, with large parts of the land being used as cropland or extensive grazing areas. Most remarkable changes are the strong expansion of the settlements as well as land management improvements. In a larger effort, ortho-mosaics covering large parts of Ethiopia in 1935-1941 will be produced

Information hiding through variance of the parametric orientation underlying a B-rep face

Watermarking technologies have been proposed for many different,types of digital media. However, to this date, no viable watermarking techniques have yet emerged for the high value B-rep (i.e. Boundary Representation) models used in 3D mechanical CAD systems. In this paper, the authors propose a new approach (PO-Watermarking) that subtly changes a model's geometric representation to incorporate a 'transparent' signature. This scheme enables software applications to create fragile, or robust watermarks without changing the size of the file, or shape of the CAD model. Also discussed is the amount of information the proposed method could transparently embed into a B-rep model. The results presented demonstrate the embedding and retrieval of text strings and investigate the robustness of the approach after a variety of transformation and modifications have been carried out on the data

Image processing for plastic surgery planning

This thesis presents some image processing tools for plastic surgery planning. In particular, it presents a novel method that combines local and global context in a probabilistic relaxation framework to identify cephalometric landmarks used in Maxillofacial plastic surgery. It also uses a method that utilises global and local symmetry to identify abnormalities in CT frontal images of the human body. The proposed methodologies are evaluated with the help of several clinical data supplied by collaborating plastic surgeons