Comments on "On Approximating Euclidean Metrics by Weighted t-Cost Distances in Arbitrary Dimension"

Mukherjee (Pattern Recognition Letters, vol. 32, pp. 824-831, 2011) recently introduced a class of distance functions called weighted t-cost distances that generalize m-neighbor, octagonal, and t-cost distances. He proved that weighted t-cost distances form a family of metrics and derived an approximation for the Euclidean norm in $\mathbb{Z}^n$. In this note we compare this approximation to two previously proposed Euclidean norm approximations and demonstrate that the empirical average errors given by Mukherjee are significantly optimistic in $\mathbb{R}^n$. We also propose a simple normalization scheme that improves the accuracy of his approximation substantially with respect to both average and maximum relative errors.Comment: 7 pages, 1 figure, 3 tables. arXiv admin note: substantial text overlap with arXiv:1008.487

Penetration Depth of a Soil Moisture Profile Probe Working in Time-Domain Transmission Mode

Soil moisture is one of the most important soil parameters. Knowledge of volumetric water content (VWC) of the root zone as well as the VWC dynamics in the soil profile is especially important for agriculture. Monitoring VWC at several depths in the soil profile can be performed using several soil moisture sensors placed at various depths. However, the use of a profile probe is more convenient, because the installation of a single probe is less disturbing to the soil, as well as less laborious and more cost-effective. The objective of the paper is to present the design and performance of a novel profile probe working in the time-domain transmission mode (P-TDT probe) with emphasis put on the penetration depth and sensitivity zone. The performance of the probe was assessed with the use of finite element method (FEM) simulations in the frequency domain, transient simulations in the time domain and laboratory experiments with the use of a vector network analyzer (VNA) working in the 10 MHz–10 GHz frequency range. It was concluded that the effective soil volume measured by the profile probe of a given geometry is equivalent to a soil thickness of about 20 mm around the tested probe. The internal part of the probe body had a negligible effect on the measurement results, as it does not change with soil moisture. Moreover, the transmitted signal amplitude was related to the soil electrical conductivity

On the AER Stereo-Vision Processing: A Spike Approach to Epipolar Matching

Image processing in digital computer systems usually considers visual information as a sequence of frames. These frames are from cameras that capture reality for a short period of time. They are renewed and transmitted at a rate of 25-30 fps (typical real-time scenario). Digital video processing has to process each frame in order to detect a feature on the input. In stereo vision, existing algorithms use frames from two digital cameras and process them pixel by pixel until it finds a pattern match in a section of both stereo frames. To process stereo vision information, an image matching process is essential, but it needs very high computational cost. Moreover, as more information is processed, the more time spent by the matching algorithm, the more inefficient it is. Spike-based processing is a relatively new approach that implements processing by manipulating spikes one by one at the time they are transmitted, like a human brain. The mammal nervous system is able to solve much more complex problems, such as visual recognition by manipulating neuron’s spikes. The spike-based philosophy for visual information processing based on the neuro-inspired Address-Event- Representation (AER) is achieving nowadays very high performances. The aim of this work is to study the viability of a matching mechanism in a stereo-vision system, using AER codification. This kind of mechanism has not been done before to an AER system. To do that, epipolar geometry basis applied to AER system are studied, and several tests are run, using recorded data and a computer. The results and an average error are shown (error less than 2 pixels per point); and the viability is proved

Multi-contrast imaging and digital refocusing on a mobile microscope with a domed LED array

We demonstrate the design and application of an add-on device for improving the diagnostic and research capabilities of CellScope--a low-cost, smartphone-based point-of-care microscope. We replace the single LED illumination of the original CellScope with a programmable domed LED array. By leveraging recent advances in computational illumination, this new device enables simultaneous multi-contrast imaging with brightfield, darkfield, and phase imaging modes. Further, we scan through illumination angles to capture lightfield datasets, which can be used to recover 3D intensity and phase images without any hardware changes. This digital refocusing procedure can be used for either 3D imaging or software-only focus correction, reducing the need for precise mechanical focusing during field experiments. All acquisition and processing is performed on the mobile phone and controlled through a smartphone application, making the computational microscope compact and portable. Using multiple samples and different objective magnifications, we demonstrate that the performance of our device is comparable to that of a commercial microscope. This unique device platform extends the field imaging capabilities of CellScope, opening up new clinical and research possibilities

Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts

This tutorial summarises our uses of reflectance transformation imaging in archaeological contexts. It introduces the UK AHRC funded project reflectance Transformation Imaging for Anciant Documentary Artefacts and demonstrates imaging methodologies

Estimating Epipolar Geometry With The Use of a Camera Mounted Orientation Sensor

Context: Image processing and computer vision are rapidly becoming more and more commonplace, and the amount of information about a scene, such as 3D geometry, that can be obtained from an image, or multiple images of the scene is steadily increasing due to increasing resolutions and availability of imaging sensors, and an active research community. In parallel, advances in hardware design and manufacturing are allowing for devices such as gyroscopes, accelerometers and magnetometers and GPS receivers to be included alongside imaging devices at a consumer level. Aims: This work aims to investigate the use of orientation sensors in the field of computer vision as sources of data to aid with image processing and the determination of a scene’s geometry, in particular, the epipolar geometry of a pair of images - and devises a hybrid methodology from two sets of previous works in order to exploit the information available from orientation sensors alongside data gathered from image processing techniques. Method: A readily available consumer-level orientation sensor was used alongside a digital camera to capture images of a set of scenes and record the orientation of the camera. The fundamental matrix of these pairs of images was calculated using a variety of techniques - both incorporating data from the orientation sensor and excluding its use Results: Some methodologies could not produce an acceptable result for the Fundamental Matrix on certain image pairs, however, a method described in the literature that used an orientation sensor always produced a result - however in cases where the hybrid or purely computer vision methods also produced a result - this was found to be the least accurate. Conclusion: Results from this work show that the use of an orientation sensor to capture information alongside an imaging device can be used to improve both the accuracy and reliability of calculations of the scene’s geometry - however noise from the orientation sensor can limit this accuracy and further research would be needed to determine the magnitude of this problem and methods of mitigation

MScMS-II: an innovative IR-based indoor coordinate measuring system for large-scale metrology applications

According to the current great interest concerning large-scale metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance are assuming a more and more important role among system requirements. This paper describes the architecture and the working principles of a novel infrared (IR) optical-based system, designed to perform low-cost and easy indoor coordinate measurements of large-size objects. The system consists of a distributed network-based layout, whose modularity allows fitting differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load. The overall system functionalities, including distributed layout configuration, network self-calibration, 3D point localization, and measurement data elaboration, are discussed. A preliminary metrological characterization of system performance, based on experimental testing, is also presente

Maskless imaging of dense samples using pixel super-resolution based multi-height lensfree on-chip microscopy.

Lensfree in-line holographic microscopy offers sub-micron resolution over a large field-of-view (e.g., ~24 mm2) with a cost-effective and compact design suitable for field use. However, it is limited to relatively low-density samples. To mitigate this limitation, we demonstrate an on-chip imaging approach based on pixel super-resolution and phase recovery, which iterates among multiple lensfree intensity measurements, each having a slightly different sample-to-sensor distance. By digitally aligning and registering these lensfree intensity measurements, phase and amplitude images of dense and connected specimens can be iteratively reconstructed over a large field-of-view of ~24 mm2 without the use of any spatial masks. We demonstrate the success of this multi-height in-line holographic approach by imaging dense Papanicolaou smears (i.e., Pap smears) and blood samples

Signal-Theoretic Characterization of Waveguide Mesh Geometries for Models of Two--Dimensional Wave Propagation in Elastic Media

Waveguide Meshes are efficient and versatile models of wave propagation along a multidimensional ideal medium. The choice of the mesh geometry affects both the computational cost and the accuracy of simulations. In this paper, we focus on 2D geometries and use multidimensional sampling theory to compare the square, triangular, and hexagonal meshes in terms of sampling efficiency and dispersion error under conditions of critical sampling. The analysis shows that the triangular geometry exhibits the most desirable tradeoff between accuracy and computational cost.Comment: 9 pages, 6 figures, 1 table, to appear on IEEE Transactions on Speech and Audio Processing, vol. 9, no. 2, february 200