Lunar regolith and substructure at Chang’E-5 landing site in the northern Oceanus Procellarum

The Lunar Regolith Penetrating Radar (LRPR) on the Chang’E-5 (CE-5) lander was deployed to investigate structures of the regolith. The migration and ridge detection methods were used to process the radar data, and the results indicate a 4.5 m regolith thickness that contains four units at the landing site, which is characterized by different internal reflections that point to their various compositions, mainly comprise protolith and admixed ejecta from the Harpalus, Copernicus, and Aristarchus. High-resolution processing for the LRPR data indicates a few rocks or slates with depth from ~ 0.2 m to over 1 m in the subsurface at the landing site, which was validated by the force analysis during the drilling of the regolith into ~ 1 m depth. The processing procedure proposed in this study is capable of producing reliable and precise images of the lunar regolith substructure, which provides important geological context on the returned drilling samples.

Automation of Ice Fractures and Calving Events Monitoring Using Medical Imaging Ridge Detection Algorithms

<p><em>Ice shelves, i.e. the floating extension of the AIS, are playing an active role in controlling ice loss from the Antarctic ice sheet. Laterally constraint in embayment or by ice rises, they are participating as regulators of the ice discharge, by exerting a back stress to the ice flow. When losing mass, these ice shelves lose their gatekeeper property, with potential local destabilization of the AIS. Losing mass from calving is a sophisticated process that is rarely coupled with observations in ice sheet models. However, calving and damages are visible in SAR remote sensing products. In this study, we built the hypothesis that state-of-the-heart ridge detection techniques from the medical imaging field can be transposed to the cryosphere field. Looking at the local Hessian matrix in SAR acquisitions, we analyzed the eigenvectors that indicate the presence of ridges. Over ice shelves, these edges correspond to the calving front of the ice shelf, or crevasses. Using time series, we can monitor the evolution of crack propagation and calving events. Results over Pine Island Glacier and the Brunt Ice Shelf show a precise delineation of calving events, as well as the damaged areas. These encouraging results support the idea of the integration of ice damage detection from SAR remote sensing into ice sheet models.</em></p>

Soft Lens Detection in Iris Image using Lens Boundary Analysis and Pattern Recognition Approach

Recent studies have demonstrated that the soft lens wearing during iris recognition has indicated the increase of false reject rate. It denies the strong belief that the soft lens wearing will cause no performance degradation. Therefore, it is a necessity for an iris recognition system to be able to detect the presence of soft lens prior to iris recognition. As a first step towards soft lens detection, this study proposed a method for segmenting the soft lens boundary in iris images. However, segmenting the soft lens boundary is a very challenging task due to its marginal contrast. Besides, the flash lighting effect during the iris image enrolment has caused the image to suffer from inconsistent illumination. In addition, the visibility condition of the soft lens boundary may be discerned as a bright or dark ridge as a result of the flash lighting. Three image enhancement techniques were therefore proposed in order to enhance the contrast of the soft lens boundary and to provide an even distribution of intensities across the image. A method called summed-histogram has been incorporated as a solution to classify the visibility condition of the soft lens boundary automatically. The visibility condition of the ridge is used to determine the directional directive magnitude by the ridge detection algorithm. The proposed method was evaluated with Notre Dame Contact Lens Detection 2013 database. Results showed that the proposed method has successfully segment the soft lens boundary with an accuracy of over 92%.

A Method for Actin Filament Tracking in Fluorescent Microscopy Images

The automated tracking of subcellular structures in live microscopy image sequences is an actual problem in many biological research areas. A universal solution for this problem still does not exist due to a huge variety of data of different nature. In this work, we propose an algorithm for tracking actin filaments in 2D fluorescent image sequences. The filaments are moving in a random and abrupt manner frequently crossing each other. We used steerable filters based ridge detection followed by crossing filaments correction algorithm for filaments detection. The tracking was performed using a greedy nearest neighbor method. The quantitative evaluation of our approach was performed on several manually annotated image sequences using the object tracking quality metric MOTA. It was shown that the proposed approach outperforms an existing approach in tracking accuracy. In addition, the proposed approach allows processing crossed filaments, unlike the existing methods.

Mapping the fracture network in the Lilstock pavement, Bristol Channel, UK: manual versus automatic

The 100 000 m2 wave-cut pavement in the Bristol Channel near Lilstock, UK, is a world-class outcrop, perfectly exposing a very large fracture network in several thin limestone layers. We present an analysis based on manual interpretation of fracture generations in selected domains and compare it with automated fracture tracing. Our dataset of high-resolution aerial photographs of the complete outcrop was acquired by an unmanned aerial vehicle, using a survey altitude optimized to resolve all fractures. We map fractures and identify fracture generations based on abutting and overprinting criteria, and we present the fracture networks of five selected representative domains. Each domain is also mapped automatically using ridge detection based on the complex shearlet transform method. The automatic fracture detection technique provides results close to the manually traced fracture networks in shorter time but with a bias towards closely spaced Y over X nodes. The assignment of fractures into generations cannot yet be done automatically, because the fracture traces extracted by the automatic method are segmented at the nodes, unlike the manual interpretation in which fractures are traced as a path from fracture tip to fracture tip and consist of several connected segments. This segmentation makes an interpretation of relative age impossible, because the identification of correct abutting relationships requires the investigation of the complete fracture trace by following a clearly defined set of rules. Generations 1 and 2 are long fractures that traverse all domains. Generation 3 is only present in the southwestern domains. Generation 4 follows an ENE–WSW striking trend, is suborthogonal to generations 1 and 2, and abuts on them and generation 3, if present. Generations 5 is the youngest fracture set with a range of orientations, creating polygonal patterns by abutting at all other fracture generations. Our mapping results show that the northeastern domains only contain four fracture generations; thus, the five generations of the outcrop identified in the southwestern domains are either not all present in each of the five domains or vary locally in their geometry, preventing the interpreter from linking the fractures to their respective generation over several spatially separate mapping domains. Fracture intensities differ between domains where the lowest is in the NE with 7.3 m−1 and the highest is in the SW with 10 m−1, coinciding with different fracture orientations and distributions of abutting relationships. Each domain has slightly different fracture network characteristics, and greater connectivity occurs where the development of later shorter fractures is not affected by the stress shadowing of pre-existing longer fractures.