Conor P. McElhinney

Extended focused imaging for digital holograms of macroscopic three-dimensional objects

When a digital hologram is reconstructed, only points located at the reconstruction distance are in focus. We have developed a novel technique for creating an in-focus image of the macroscopic objects encoded in a digital hologram. This extended focused image is created by combining numerical reconstructions with depth information extracted by using our depth-from-focus algorithm. To our knowledge, this is the first technique that creates extended focused images of digital holograms encoding macroscopic objects. We present results for digital holograms containing low- and high-contrast macroscopic objects.

Reconstruction of partially occluded objects encoded in three-dimensional scenes by using digital holograms

We propose a task-specific digital holographic capture system for three-dimensional scenes, which can reduce the amount of data sent from the camera system to the receiver and can effectively reconstruct partially occluded objects. The system requires knowledge of the object of interest, but it does not require a priori knowledge of either the occlusion or the distance the object is from the camera. Subwindows of the camera-plane Fresnel field are digitally propagated to reveal different perspectives of the scene, and these are combined to overcome the unknown foreground occlusions. The nature of the occlusions and the effect of subwindows are analyzed thoroughly by using the Wigner distribution function. We demonstrate that a careful combination of reconstructions from subwindows can reveal features that are not apparent in a reconstruction from the whole hologram. We provide results by using optically captured digital holograms of real-world objects and simulated occlusions.

Depth-independent segmentation of macroscopic three-dimensional objects encoded in single perspectives of digital holograms

We present a technique for performing segmentation of macroscopic three-dimensional objects recorded using in-line digital holography. We numerically reconstruct a single perspective of each object at a range of depths. At each point in the digital wavefront we calculate variance about a neighborhood. The maximum variance at each point over all depths is thresholded to classify it as an object pixel or a background pixel. Segmentation results for objects of low and high contrast are presented.

Automated road markings extraction from mobile laser scanning data

Abstract Road markings are used to provide guidance and instruction to road users for safe and comfortable driving. Enabling rapid, cost-effective and comprehensive approaches to the maintenance of route networks can be greatly improved with detailed information about location, dimension and condition of road markings. Mobile Laser Scanning (MLS) systems provide new opportunities in terms of collecting and processing this information. Laser scanning systems enable multiple attributes of the illuminated target to be recorded including intensity data. The recorded intensity data can be used to distinguish the road markings from other road surface elements due to their higher retro-reflective property. In this paper, we present an automated algorithm for extracting road markings from MLS data. We describe a robust and automated way of applying a range dependent thresholding function to the intensity values to extract road markings. We make novel use of binary morphological operations and generic knowledge of the dimensions of road markings to complete their shapes and remove other road surface elements introduced through the use of thresholding. We present a detailed analysis of the most applicable values required for the input parameters involved in our algorithm. We tested our algorithm on different road sections consisting of multiple distinct types of road markings. The successful extraction of these road markings demonstrates the effectiveness of our algorithm.

A Projection System for Real World Three-Dimensional Objects Using Spatial Light Modulators

We discuss a projection system for real world three-dimensional objects using spatial light modulators (SLM). An algorithm to encode the digital holograms of real world objects on to an SLM is presented. We present results from experiments to project holograms of real world holograms using a nematic liquid crystal SLM. We discuss the case when the pixel sizes of the charge-coupled device (CCD) and SLM used for recording the hologram and projection are different.

A Practical Guide to Digital Holography and Generalized Sampling

The theorems of Nyquist, Shannon and Whittaker have long held true for sampling optical signals. They showed that a signal (with finite bandwidth) should be sampled at a rate at least as fast as twice the maximum spatial frequency of the signal. They proceeded to show how the continuous signal could be reconstructed perfectly from its well sampled counterpart by convolving a Sinc function with the sampled signal. Recent years have seen the emergence of a new generalized sampling theorem of which Nyquist Shannon is a special case. This new theorem suggests that it is possible to sample and reconstruct certain signals at rates much slower than those predicted by Nyquist-Shannon. One application in which this new theorem is of considerable interest is Fresnel Holography. A number of papers have recently suggested that the sampling rate for the digital recording of Fresnel holograms can be relaxed considerably. This may allow the positioning of the object closer to the camera allowing for a greater numerical aperture and thus an improved range of 3D perspective. In this paper we: (i) Review generalized sampling for Fresnel propagated signals, (ii) Investigate the effect of the twin image, always present in recording, on the generalized sampling theorem and (iii) Discuss the effect of finite pixel size for the first time.

Removing the twin image in digital holography by segmented filtering of in-focus twin image

We propose and investigate a new digital method for the reduction of twin-image noise from digital Fresnel holograms. For the case of in-line Fresnel holography the unwanted twin is present as a highly corruptive noise when the object image is numerically reconstructed. We propose to firstly reconstruct the unwanted twin-image when it is in-focus and in this plane we calculate a segmentation mask that borders this in focus image. The twin-image is then segmented and removed by simple spatial filtering. The resulting digital wavefield is the inverse propagated to the desired object image plane. The image is free of the twin-image resulting in improved quality reconstructions. We demonstrate the segmentation and removal of the unwanted twin-image from in-line digital holograms containing real-world macroscopic objects. We offer suggestions for its rapid computational implementation.

Calculation of Target-Specific Point Distribution for 2D Mobile Laser Scanners

The current generation of Mobile Mapping Systems (MMSs) capture high density spatial data in a short time-frame. The quantity of data is difficult to predict as there is no concrete understanding of the point density that different scanner configurations and hardware settings will exhibit for objects at specific distances. Obtaining the required point density impacts survey time, processing time, data storage and is also the underlying limit of automated algorithms. This paper details a novel method for calculating point and profile information for terrestrial MMSs which are required for any point density calculation. Through application of algorithms utilising 3D surface normals and 2D geometric formulae, the theoretically optimal profile spacing and point spacing are calculated on targets. Both of these elements are a major factor in calculating point density on arbitrary objects, such as road signs, poles or buildings-all important features in asset management surveys.

Mobile Mapping System LiDAR Data Framework

Mobile Mapping Systems (MMSs) for infrastructural monitoring and mapping are becoming more prevalent as the availability and affordability of solutions that generate high accuracy geospatial data has matured. However, no existent methodology or system exists where all the LiDAR, video, navigation, infrared and multispectral data sources, collected from this mobile platform, are integrated into a single, comprehensive data management solution. Based on empirical experience there is a need for an MMS-data management framework where these types of data can be dynamically accessed and integrated to enable different projects with varying objectives to dynamically access different MMS-data for, in one example, use in feature extraction algorithms. In this paper we introduce the LiDAR aspect of this work towards a MMS-data framework. With large volumes of LiDAR to be stored we have opted for a spatially enabled database (SDB) management solution, specifically PostgreSQL with PostGIS extensions. We detail our approach to storing and querying the LiDAR data in the SDB and provide preliminary results on query times and data returns.

Snake Energy Analysis and Result Validation for a Mobile Laser Scanning Data-Based Automated Road Edge Extraction Algorithm

The negative impact of road accidents cannot be ignored in terms of the very sizeable social and economic loss. Road infrastructure has been identified as one of the main causes of the road accidents. They are required to be recorded, located, measured, and classified in order to schedule maintenance and identify the possible risk elements of the road. Toward this, an accurate knowledge of the road edges increases the reliability and precision of extracting other road features. We have developed an automated algorithm for extracting road edges from mobile laser scanning (MLS) data based on the parametric active contour or snake model. The algorithm involves several internal and external energy parameters that need to be analyzed in order to find their optimal values. In this paper, we present a detailed analysis of the snake energy parameters involved in our road edge extraction algorithm. Their optimal values enable us to automate the process of extracting edges from MLS data for tested road sections. We present a modified external energy in our algorithm and demonstrate its utility for extracting road edges from low and nonuniform point density datasets. A novel validation approach is presented, which provides a qualitative assessment of the extracted road edges based on direct comparisons with reference road edges. This approach provides an alternative to traditional road edge validation methodologies that are based on creating buffer zones around reference road edges and then computing quality measure values for the extracted edges. We tested our road edge extraction algorithm on datasets that were acquired using multiple MLS systems along various complex road sections. The successful extraction of road edges from these datasets validates the robustness of our algorithm for use in complex route corridor environments.