Image Patch-Matching With Graph-Based Learning in Street Scenes.

Matching landmark patches from a real-time image captured by an on-vehicle camera with landmark patches in an image database plays an important role in various computer perception tasks for autonomous driving. Current methods focus on local matching for regions of interest and do not take into account spatial neighborhood relationships among the image patches, which typically correspond to objects in the environment. In this paper, we construct a spatial graph with the graph vertices corresponding to patches and edges capturing the spatial neighborhood information. We propose a joint feature and metric learning model with graph-based learning. We provide a theoretical basis for the graph-based loss by showing that the information distance between the distributions conditioned on matched and unmatched pairs is maximized under our framework. We evaluate our model using several street-scene datasets and demonstrate that our approach achieves state-of-the-art matching results.

An improved tamper detection and localization scheme for volumetric DICOM images.

The development of teleradiology brings the convenience of global medical record access along with the concerns over the security of medical images transmitted over the open network. With the prevailing adoption of three-dimensional (3-D) imaging modalities, it is vital to develop a security mechanism to provide large volumes of medical images with privacy and reliability. This paper presents the development of a new and improved method of implementing tamper detection and localization based on a fully reversible digital watermarking scheme for the protection of volumetric DICOM images. This tamper detection and localization method utilizes the 3-D property of volumetric data to achieve much faster processing time at both sender and receiver sides without compromising tamper localization accuracy. The performance of the proposed scheme was evaluated by using sample volumetric DICOM images. Results show that the scheme achieved on average about 65 % and 72 % reduction in watermarking and dewatermarking processing time, respectively. For cases where the images had been tampered, it is possible to detect and localize the tampered areas with improved localization resolution in the images using the scheme.

Security protection of DICOM medical images using dual-layer reversible watermarking with tamper detection capability.

Teleradiology applications and universal availability of patient records using web-based technology are rapidly gaining importance. Consequently, digital medical image security has become an important issue when images and their pertinent patient information are transmitted across public networks, such as the Internet. Health mandates such as the Health Insurance Portability and Accountability Act require healthcare providers to adhere to security measures in order to protect sensitive patient information. This paper presents a fully reversible, dual-layer watermarking scheme with tamper detection capability for medical images. The scheme utilizes concepts of public-key cryptography and reversible data-hiding technique. The scheme was tested using medical images in DICOM format. The results show that the scheme is able to ensure image authenticity and integrity, and to locate tampered regions in the images.

High capacity DNA data storage with variable-length Oligonucleotides using repeat accumulate code and hybrid mapping.

BACKGROUND: With the inherent high density and durable preservation, DNA has been recently recognized as a distinguished medium to store enormous data over millennia. To overcome the limitations existing in a recently reported high-capacity DNA data storage while achieving a competitive information capacity, we are inspired to explore a new coding system that facilitates the practical implementation of DNA data storage with high capacity. RESULT: In this work, we devised and implemented a DNA data storage scheme with variable-length oligonucleotides (oligos), where a hybrid DNA mapping scheme that converts digital data to DNA records is introduced. The encoded DNA oligos stores 1.98 bits per nucleotide (bits/nt) on average (approaching the upper bound of 2 bits/nt), while conforming to the biochemical constraints. Beyond that, an oligo-level repeat-accumulate coding scheme is employed for addressing data loss and corruption in the biochemical processes. With a wet-lab experiment, an error-free retrieval of 379.1 KB data with a minimum coverage of 10x is achieved, validating the error resilience of the proposed coding scheme. Along with that, the theoretical analysis shows that the proposed scheme exhibits a net information density (user bits per nucleotide) of 1.67 bits/nt while achieving 91% of the information capacity. CONCLUSION: To advance towards practical implementations of DNA storage, we proposed and tested a DNA data storage system enabling high potential mapping (bits to nucleotide conversion) scheme and low redundancy but highly efficient error correction code design. The advancement reported would move us closer to achieving a practical high-capacity DNA data storage system.

An impulse radio ultrawideband system for contactless noninvasive respiratory monitoring.

We design a impulse radio ultrawideband radar monitoring system to track the chest wall movement of a human subject during respiration. Multiple sensors are placed at different locations to ensure that the backscattered signal could be detected by at least one sensor no matter which direction the human subject faces. We design a hidden Markov model to infer the subject facing direction and his or her chest movement. We compare the performance of our proposed scheme on 15 human volunteers with the medical gold standard using respiratory inductive plethysmography (RIP) belts, and show that on average, our estimation is over 81% correlated with the measurements of a RIP belt system. Furthermore, in order to automatically differentiate between periods of normal and abnormal breathing patterns, we develop a change point detection algorithm based on perfect simulation techniques to detect changes in the subject's breathing. The feasibility of our proposed system is verified by both the simulation and experiment results.