Multi-Scale Vector-Ridge-Detection for Perceptual Organization Without Edges

We present a novel ridge detector that finds ridges on vector fields. It is designed to automatically find the right scale of a ridge even in the presence of noise, multiple steps and narrow valleys. One of the key features of such ridge detector is that it has a zero response at discontinuities. The ridge detector can be applied to scalar and vector quantities such as color. We also present a parallel perceptual organization scheme based on such ridge detector that works without edges; in addition to perceptual groups, the scheme computes potential focus of attention points at which to direct future processing. The relation to human perception and several theoretical findings supporting the scheme are presented. We also show results of a Connection Machine implementation of the scheme for perceptual organization (without edges) using color.

Fast power line detection and localization using steerable filter for active UAV guidance

In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

A novel representation of bioacoustic events for content-based search in field audio data

Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.

Similarity-based birdcall retrieval from environmental audio

Automated digital recordings are useful for large-scale temporal and spatial environmental monitoring. An important research effort has been the automated classification of calling bird species. In this paper we examine a related task, retrieval of birdcalls from a database of audio recordings, similar to a user supplied query call. Such a retrieval task can sometimes be more useful than an automated classifier. We compare three approaches to similarity-based birdcall retrieval using spectral ridge features and two kinds of gradient features, structure tensor and the histogram of oriented gradients. The retrieval accuracy of our spectral ridge method is 94% compared to 82% for the structure tensor method and 90% for the histogram of gradients method. Additionally, this approach potentially offers a more compact representation and is more computationally efficient.

Generalised features for bird vocalisation retrieval in acoustic recordings

Bioacoustic monitoring has become a significant research topic for species diversity conservation. Due to the development of sensing techniques, acoustic sensors are widely deployed in the field to record animal sounds over a large spatial and temporal scale. With large volumes of collected audio data, it is essential to develop semi-automatic or automatic techniques to analyse the data. This can help ecologists make decisions on how to protect and promote the species diversity. This paper presents generic features to characterize a range of bird species for vocalisation retrieval. In the implementation, audio recordings are first converted to spectrograms using short-time Fourier transform, then a ridge detection method is applied to the spectrogram for detecting points of interest. Based on the detected points, a new region representation are explored for describing various bird vocalisations and a local descriptor including temporal entropy, frequency bin entropy and histogram of counts of four ridge directions is calculated for each sub-region. To speed up the retrieval process, indexing is carried out and the retrieved results are ranked according to similarity scores. The experiment results show that our proposed feature set can achieve 0.71 in term of retrieval success rate which outperforms spectral ridge features alone (0.55) and Mel frequency cepstral coefficients (0.36).

Birdcall retrieval from environmental acoustic recordings using image processing

Acoustic recordings of the environment provide an effective means to monitor bird species diversity. To facilitate exploration of acoustic recordings, we describe a content-based birdcall retrieval algorithm. A query birdcall is a region of spectrogram bounded by frequency and time. Retrieval depends on a similarity measure derived from the orientation and distribution of spectral ridges. The spectral ridge detection method caters for a broad range of birdcall structures. In this paper, we extend previous work by incorporating a spectrogram scaling step in order to improve the detection of spectral ridges. Compared to an existing approach based on MFCC features, our feature representation achieves better retrieval performance for multiple bird species in noisy recordings.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

Image processing chip for small object detection

A new, front-end image processing chip is presented for real-time small object detection. It has been implemented using a 0.6 µ, 3.3 V CMOS technology and operates on 10-bit input data at 54 megasamples per second. It occupies an area of 12.9 mm×13.6 mm (including pads), dissipates 1.5 W, has 92 I/O pins and is to be housed in a 160-pin ceramic quarter flat-pack. It performs both one- and two-dimensional FIR filtering and a multilayer perceptron (MLP) neural network function using a reconfigurable array of 21 multiplication-accumulation cells which corresponds to a window size of 7×3. The chip can cope with images of 2047 pixels per line and can be cascaded to cope with larger window sizes. The chip performs two billion fixed point multiplications and additions per second.

Hydrobiogeochemical Interactions along “Flow Tubes” Controls: Watershed Scale Contaminant Flow and Transformation at the Oak Ridge IFRC

Geochemical,spectrographic, microbiological and hydrogeologic studies at the ORIFRC site indicate that groundwater transport in structured media may behave as a system of parallel flow tubes. These tubes are preferred flowpaths that enable contaminant transport parallel to bedding planes (strike) over distances of 1000s of meters. A significant flux of groundwater is focused within an interval defined by the interface between the competent bedrock and overlying highly-weathered saprolite, commonly referred to as the"transition zone." Characteristics of this transition zone are dense fractures and the relative absence of weathering products (e.g. clays)results in a significantly higher permeability compared to both the overlying clay-saprolite and underlying bedrock. Several stratabound low seismic velocity zones located below the transition zone were identified during geophysics studies and were also determined to be fractured high permeability preferred contaminant transport pathways during subsequent drilling activities. XANES analysis of precipitates collected from these deeper flow zones indicate 95% or more of the U deposited is U(VI). Linear combination fitting of the EXAFS data shows that precipitates are ~51±5% U(VI)-carbonate-like phase (e.g., liebigite) and ~49±5% U(VI) associated with an iron oxide phase; inclusion of a third component in the fit suggests that up to 15% of the U(VI) may be associated with a phosphate phase or OH- phase (e.g.,schoepite). Although precipitates with similar U(VI)-carbonate and/or phosphate associations were identified in the transition zone pathways,there were also U(VI) complexes adsorbed to mineral surfaces that would tend to be more readily mobilized. Groundwater in the different flow tubes has been determined to consist of different water quality types that vary with the solid phase encountered (e.g., clays, carbonates, clastics) as contaminants migrate along the flow paths. This lateral and vertical variability in geochemistry, particularly pH, has a significant impact on microbiological community composition and activity. Ribosomal RNA gene analyses coupled with physiological and genomic analyses suggest that bacteria from the genus Rhodanobacter(a diverse population of denitrifiers that are moderately acid tolerant) have a high relative abundance in the acidic source zone at the ORIFRC site.Watershed-scale analysis across different flow paths/tubes revealed strong negative correlation between pH and the absolute and relative abundance of Rhodanobacter. Recent studies also confirmed that the ORIFRC site hosts a diverse fungal community, with significant differences observed between acidic (pH <5) and circumneutral (>5) wells. The lack of nitrous oxide reduction capability in fungi, and the detection of denitrification potential in slurry microcosms suggest that fungi may have aheretofore under appreciated role in biogeochemical transformations, with implications forsite remediation and greenhouse gas emissions. Further research is needed to determine if these organisms can influence U(VI) mobility either directly through immobilization or indirectly through the depletion of nitrate.In conclusion, additional studies are required to quantify the processes (e.g., solid phase reactions, recharge, diffusion, microbial interactions) that are occurring along the groundwater flow tubes identified at the ORIFRC so predictive models can be parameterized and used to assess long-term contaminant fate and transport and remedial options.

Lawsone : a novel reagent for the detection of latent fingermarks on paper surfaces

Lawsone (2-hydroxy-1,4-naphthoquinone) reacts with latent fingermark deposits on paper surfaces to yield purple-brown impressions of ridge details which are also photoluminescent; this compound represents the first in a completely new class of fingermark detection reagents.

Chemical composition of Ninetyeast Ridge basalts

On Leg 121 of the Ocean Drilling Program, we recovered basaltic rocks from a total of three basement sites in the southern, central, and northern regions of Ninetyeast Ridge. These new sites complement the previous four basement holes drilled during Legs 22 and 26 of the Deep Sea Drilling Project, and confirm the predominantly tholeiitic, light rare earth element-enriched character of the basalts that cap the ridge. The basalts show marked iron enrichment; ferrobasalts occur at Sites 214 and 216 and oceanic andesites at Site 253. All of the basalts recovered during Leg 121 are altered, and range from aphyric olivine tholeiites (Site 756), to strongly plagioclase-phyric basalts (Site 757). Basalts from Site 758, which were clearly erupted in a submarine environment (pillow basalts are present in the section), are sparsely to strongly plagioclase-phyric. The basalts recovered at any one hole are isotopically homogeneous (except for the basalts from Site 758, which show a range of Pb isotopes), and it is possible to relate the magmas at any one site by high-level fractionation processes. However, there are significant variations in isotope ratios and highly incompatible element ratios between sites, which suggest that the mantle source for the ridge basalts was compositionally variable. Such variation, in view of the large volume of magmatic products that form the ridge system, is not surprising. There is not, however, a systematic variation in basalt composition along the ridge. We agree with previous models that relate Ninetyeast Ridge to a mantle plume in the southern Indian Ocean. The tholeiitic, iron-enriched, and voluminous character of the ridge basalts is typical of oceanic islands associated with plumes on or near a mid-ocean ridge (e.g., Iceland, Galapagos Islands, and St. Paul/Amsterdam islands). The absence of recovered alkalic suites is inconsistent with an intraplate setting, such as the Hawaiian Islands or Kerguelen Island. Thus, the major element data, like the gravity data, strongly suggest that the ridge was erupted on or very close to an active spreading center. Isotopically, the most likely plume that created the excess magmatism on the Ridge is the Kerguelen-Heard plume system, but the Ninetyeast Ridge basalts do not represent a simple mixing of the Kerguelen plume and mid-ocean Ninetyeast Ridge basalt mantle.

(Table 3) Relative content of n-alkane groups in samples from hydrothermal fields of the Mid-Atlantic Ridge

Optimum conditions were selected for chromatographic separation of model mixtures of C12-C40 n-alkanes. For one of samples of hydrothermal deposits extraction conditions of hydrocarbons were studied and a sample preparation procedure was selected. The procedure was proposed to determine n-alkanes in samples of hydrothermal deposits by means of gas chromatography - mass spectrometry (GC-MS). Detection limit for n-alkanes was 3x10**-9 to 10**-8% depending on components. On the basis of the proposed procedure composition of n-alkanes was studied in samples of hydrothermal deposits collected at the Mid-Atlantic Ridge (Broken Spur, Lost City, and Rainbow hydrothermal fields). Analyses showed that samples contained C14-C35 n-alkanes. Concentrations of the n-alkanes were rather low and varied from 0.002 to 0.038 µg/g. Hypotheses concerning genesis of identified n-alkanes were offered.

Foraminifera in sediment cores of the Lomonosov Ridge and Morris Jesup Rise

X-ray fluorescence (XRF) scanning of sediment cores from the Lomonosov Ridge and the Morris Jesup Rise reveals a distinct pattern of Ca intensity peaks through Marine Isotope Stages (MIS) 1 to 7. Downcore of MIS 7, the Ca signal is more irregular and near the detection limit. Virtually all major peaks in Ca coincide with a high abundance of calcareous microfossils; this is particularly conspicuous in the cores from the central Arctic Ocean. However, the recorded Ca signal is generally caused by a combination of biogenic and detrital carbonate, and in areas influenced by input from the Canadian Arctic, detrital carbonates may effectively mask the foraminiferal carbonates. Despite this, there is a strong correlation between XRF-detected Ca content and foraminiferal abundance. We propose that in the Arctic Ocean north of Greenland a common palaeoceanographic mechanism is controlling Ca-rich ice-rafted debris (IRD) and foraminiferal abundance. Previous studies have shown that glacial periods are characterized by foraminfer-barren sediments. This implies that the Ca-rich IRD intervals with abundant foraminifera were most likely deposited during interglacial periods when glaciers left in the Canadian Arctic Archipelago were still active and delivered a large amount of icebergs. At the same time, conditions were favourable for planktic foraminifera, resulting in a strong covariance between these proxies. Therefore, we suggest that the XRF scanner's capability to efficiently map Ca concentrations in sediment cores makes it possible to systematically examine large numbers of cores from different regions to investigate the palaeoceanographic reasons for the calcareous microfossils' spatial and temporal variability.

Bibliography [of] radiation detection.

"Prepared by the Radiation Instruments Branch, Washington Division of Production, U. S. Atomic Energy Commission."