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Automatic detection, tracking and counting of birds in marine video content

Automatic detection, tracking and counting of birds in marin...

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6th International conference on image processing Theory, Tools and applications (IPTA)

作者： T'Jampens, Roeland Hernandez, Francisco Vandecasteele, Florian Verstockt, Steven Flanders Marine Inst VLIZ Wandelaarkaai 7 B-8400 Oostende Belgium UGent iMinds Data Sci Lab Sint Pietersnieuwstr 41 B-9000 Ghent Belgium

ISBN: (纸本)9781467389105

Robust automatic detection of moving objects in a marine context is a multi-faceted problem due to the complexity of the observed scene. The dynamic nature of the sea caused by waves, boat wakes, and weather conditions poses huge challenges for the development of a stable background model. Moreover, camera motion, reflections, lightning and illumination changes may contribute to false detections. Dynamic background subtraction (DBGS) is widely considered as a solution to tackle this issue in the scope of vessel detection for maritime traffic analysis. In this paper, the DBGS techniques suggested for ships are investigated and optimized for the monitoring and tracking of birds in marine video content. In addition to background subtraction, foreground candidates are filtered by a classifier based on their feature descriptors in order to remove non-bird objects. Different types of classifiers have been evaluated and results on a ground truth labeled dataset of challenging video fragments show similar levels of precision and recall of about 95% for the best performing classifier. The remaining foreground items are counted and birds are tracked along the video sequence using spatio-temporal motion prediction. This allows marine scientists to study the presence and behavior of birds.

关键词： dynamic background subtraction texture analysis image classification object detection tracking seabirds marine environment

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Optical remote sensing and correlation of office equipment functional state and stress levels via power quality disturbances inefficiencies 39

Optical remote sensing and correlation of office equipment f...

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conference on applications of Digital image processing xxxIx

作者： Sternberg, Oren Bednarski, Valerie R. Perez, Israel Wheeland, Sara Rockway, John D. SPAWAR Syst Ctr Pacific 53560 Hull St San Diego CA 92152 USA

ISBN: (数字)9781510603349

ISBN: (纸本)9781510603332;9781510603349

Non-invasive optical techniques pertaining to the remote sensing of power quality disturbances (PQD) are part of an emerging technology field typically dominated by radio frequency (RF) and invasive-based techniques. Algorithms and methods to analyze and address PQD such as probabilistic neural networks and fully informed particle swarms have been explored in industry and academia. Such methods are tuned to work with RF equipment and electronics in existing power grids. As both commercial and defense assets are heavily power-dependent, understanding electrical transients and failure events using non-invasive detection techniques is crucial. In this paper we correlate power quality empirical models to the observed optical response. We also empirically demonstrate a first-order approach to map household, office and commercial equipment PQD to user functions and stress levels. We employ a physics-based image and signal processing approach, which demonstrates measured non-invasive (remote sensing) techniques to detect and map the base frequency associated with the power source to the various PQD on a calibrated source.

关键词： remote sensing power quality disturbances image processing

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ISR Systems - Past, Present, and Future 13

ISR Systems - Past, Present, and Future

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conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and applications xIII

作者： Henry, Daniel J. Rockwell Collins Inc Cedar Rapids IA 52498 USA

ISBN: (纸本)9781510600690

Intelligence, Surveillance, and Reconnaissance (ISR) systems have been in use for thousands of years. Technology and CONOPS have continually evolved and morphed to meet ever-changing information needs and adversaries. Funding sources, constraints and procurement philosophies have also evolved, requiring cost-effective innovation to field marketable products which maximize the effectiveness of the Tasking, Capture, processing, Exploitation, and Dissemination (TCPED) information chain. This paper describes the TCPED information chain and the evolution of ISR (past, present, and future).

关键词： Intelligence systems Intelligence systems Data storage Brain image processing Surveillance Data communications Sensors Reconnaissance Reconnaissance systems Reconnaissance systems signal processing

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Optical Techniques for Sound processing 19

Optical Techniques for Sound Processing

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19th Annual conference on Novel Optical Systems Design and Optimization

作者： Kraft, Sebastian Eichas, Felix Zoelzer, Udo Helmut Schmidt Univ Signal Proc & Communicat Holstenhofweg 85 D-22043 Hamburg Germany

ISBN: (数字)9781510602885

ISBN: (纸本)9781510602878;9781510602885

This contribution provides an overview of optical techniques for sound recording, sound synthesis, and sound processing. Several applications of optical devices, examples, and references describing the history and current trends in this field will be given. For sound recording, optical devices can be used to capture vibrations and to transform mechanical sound waves into an electrical signal. Optical storage of audio has a long history beginning with analog sound tracks on film up to recent optical media as for example the Blue-ray Disc. For sound synthesis based on optical systems we will give examples based on graphical sound and the photo-sonic disc for time-domain synthesis. Frequency-domain synthesis techniques which are controlled by a time-frequency (image domain) signal representation will be explained. For analog sound processing the use of a light emitting diode coupled to a photo-electric cell (light dependent resistor) constitutes a nonlinear two-port electrical network or element. These optocouplers have still a wide range of applications for switching, gating, and volume control of audio signals due to their special nonlinear behavior. Hence, there exists a broad interest for high-quality discrete-time models of these devices. An overview of several applications with these optical nonlinearities will be given.

关键词： Optical devices optical sound recording optical sound synthesis optical sound processing nonlinear optical elements

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Gabor Barcodes for Medical image Retrieval 23

Gabor Barcodes for Medical Image Retrieval

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23rd IEEE International conference on image processing (ICIP)

作者： Nouredanesh, Mina Tizhoosh, Hamid R. Banijamali, Ershad Univ Waterloo Dept Mech & Mechatron Engn Waterloo ON N2L 3G1 Canada Univ Waterloo KIMIA Lab Waterloo ON N2L 3G1 Canada Univ Waterloo Cheriton Sch Comp Sci Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781467399616

In recent years, advances in medical imaging have led to the emergence of massive databases, containing images from a diverse range of modalities. This has significantly heightened the need for automated annotation of the images on one side, and fast and memory-efficient content-based image retrieval systems on the other side. Binary descriptors have recently gained more attention as a potential vehicle to achieve these goals. One of the recently introduced binary descriptors for tagging of medical images are Radon barcodes (RBCs) that are driven from Radon transform via local thresholding. Gabor transform is also a powerful transform to extract texture-based information. Gabor features have exhibited robustness against rotation, scale, and also photometric disturbances, such as illumination changes and image noise in many applications. This paper introduces Gabor Barcodes (GBCs), as a novel framework for the image annotation. To find the most discriminative GBC for a given query image, the effects of employing Gabor filters with different parameters, i.e., different sets of scales and orientations, are investigated, resulting in different barcode lengths and retrieval performances. The proposed method has been evaluated on the IRMA dataset with 193 classes comprising of 12,677 x-ray images for indexing, and 1,733 x-rays images for testing. A total error score as low as 351 (approximate to 80% accuracy for the first hit) was achieved.

关键词： Content-based image retrieval CBIR binary codes Radon barcodes Radon transform Gabor Transform image annotation Hamming distance

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Supervised sparse-representation classification on hyperspectral images using the city-block distance to improve performance

Supervised sparse-representation classification on hyperspec...

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8th International conference of Pattern Recognition Systems (ICPRS 2017)

作者： Fernando x. Arias Heidy Sierra Luis O. Jimenez-Rodriguez Emmanuel Arzuaga Universidad de Puerto Rico San Juan PR

ISBN: (纸本)9781785616525

Hyperspectral images' data structure contains information from spectral ranges far beyond the limits of conventional, visible light imaging devices. This additional information comes at the cost of having unwieldy large image sizes, which presents an important computational resource consideration for many applications. Recent studies have shown that the usual large amount of redundancy in Hyperspectral images can be discarded to avoid classification noise by means of sparse signal processing principles. To improve on classification performance, class-dependent Sparse-Representation classification (cd-SRC) algorithm includes Euclidean distance information between the sparse representation of a sample pixel to be classified and the training classes. The current work describes the use of Manhattan (or City Block) distance for improving the cd-SRC classification procedure. Our results show that classification performance using Euclidean Distance is comparable to the Manhattan Distance metric, which requires a smaller number of significantly less computationally expensive operations. In addition, we show that sparse representation classification has a significant advantage in classification performance compared to established Hyperspectral image classification algorithms, such as the well-known Minimum Euclidean Distance and Support Vector Machine classifiers.

关键词： compressed sensing data structures hyperspectral imaging image classification visible spectra hyperspectral imagery VISIBLE SPECTRUM Data structures Compressed sensing image classification Euclidean distance sparse representation Taxonomy Manhattan city blocks Support Vector Network

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An end-user-oriented framework for RGB representation of multitemporal SAR images and visual datamining 22

An end-user-oriented framework for RGB representation of mul...

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conference on image and signal processing for Remote Sensing xxII

作者： Amitrano, Donato Cecinati, Francesca Di Martino, Gerardo Iodice, Antonio Mathieu, Pierre-Philippe Riccio, Daniele Ruello, Giuseppe Univ Naples Federico II Dept Elect Elect & Informat Technol Via Claudio 21 I-80125 Naples Italy European Space Agcy ESA ESRIN Via Galileo Galilei I-00044 Frascati Italy

ISBN: (数字)9781510604131

ISBN: (纸本)9781510604124;9781510604131

In this paper, we present a new framework for the generation of two new classes of RGB products derived from multitemporal SAR data. The aim of our processing chain is to provide products characterized by a high degree of interpretability (thanks to a consistent rendering of the underlying electromagnetic scattering mechanisms) and by the possibility to be exploited in combination with simple algorithms for information extraction. The physical rationale of the proposed RGB products is presented through examples highlighting their principal properties. Finally, the suitability of these products with applications is demonstrated through two examples dealing with feature extraction and classification activities. (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

关键词： synthetic aperture radar self-organizing maps image enhancement classification multitemporal SAR Level-1 alpha products Level-1 beta products

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HIGH CONTRAST IMAGING THROUGH ADAPTIVE TRANSMITTANCE CONTROL IN THE FOCAL PLANE 5

HIGH CONTRAST IMAGING THROUGH ADAPTIVE TRANSMITTANCE CONTROL...

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conference on Dimensional Optical Metrology and Inspection for Practical applications V

作者： Dhadwal, Harbans S. Rastegar, Jahangir Feng, Dake Omnitek Partners LLC Unit 3 Ronkonkoma NY 11779 USA

ISBN: (纸本)9781510601093

High contrast imaging, in the presence of a bright background, is a challenging problem encountered in diverse applications ranging from the daily chore of driving into a sun-drenched scene to in vivo use of biomedical imaging in various types of keyhole surgeries. Imaging in the presence of bright sources saturates the vision system, resulting in loss of scene fidelity, corresponding to low image contrast and reduced resolution. The problem is exacerbated in retro-reflective imaging systems where the light sources illuminating the object are unavoidably strong, typically masking the object features. This manuscript presents a novel theoretical framework, based on nonlinear analysis and adaptive focal plane transmittance, to selectively remove object domain sources of background light from the image plane, resulting in local and global increases in image contrast. The background signal can either be of a global specular nature, giving rise to parallel illumination from the entire object surface or can be represented by a mosaic of randomly orientated, small specular surfaces. The latter is more representative of real world practical imaging systems. Thus, the background signal comprises of groups of oblique rays corresponding to distributions of the mosaic surfaces. Through the imaging system, light from group of like surfaces, converges to a localized spot in the focal plane of the lens and then diverges to cast a localized bright spot in the image plane. Thus, transmittance of a spatial light modulator, positioned in the focal plane, can be adaptively controlled to block a particular source of background light. Consequently, the image plane intensity is entirely due to the object features. Experimental image data is presented to verify the efficacy of the methodology.

关键词： Fourier optics optical signal processing image contrast bright field imaging

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Simultenious binary hash and features learning for image retrieval

Simultenious binary hash and features learning for image ret...

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conference on Mobile Multimedia/image processing, Security, and applications

作者： Frantc, V. A. Makov, S., V Voronin, V. V. Marchuk, V., I Semenishchev, E. A. Egiazarian, K. O. Agaian, S. Don State Tech Univ Dept Radioelect Syst Gagarina 1 Rostov Na Donu Russia Tampere Univ Technol Dept Signal Proc Korkeakoulunkatu 1 Tampere Finland Univ Texas San Antonio San Antonio TX USA

ISBN: (纸本)9781510601109

Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo collection management systems, web scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel based image representation to hash value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state of the art methods.

关键词： content-based image retrieval deep convolutional neural network semantic hashing autoencoder

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Binary CMOS image Sensor with a Gate/Body-Tied MOSFET-Type Photodetector for High-Speed Operation 3

Binary CMOS Image Sensor with a Gate/Body-Tied MOSFET-Type P...

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conference on image Sensing Technologies - Materials, Devices, Systems, and applications III

作者： Choi, Byoung-Soo Jo, Sung-Hyun Bae, Myunghan Kim, Sang-Hwan Shin, Jang-Kyoo Kyungpook Natl Univ Sch Elect Engn 80 Daehakro Daegu 702701 South Korea

ISBN: (纸本)9781510600959

In this paper, a binary complementary metal oxide semiconductor (CMOS) image sensor with a gate/body-tied (GBT) metal oxide semiconductor field effect transistor (MOSFET)-type photodetector is presented. The sensitivity of the GBT MOSFET-type photodetector, which was fabricated using the standard CMOS 0.35-mu m process, is higher than the sensitivity of the p-n junction photodiode, because the output signal of the photodetector is amplified by the MOSFET. A binary image sensor becomes more efficient when using this photodetector. Lower power consumptions and higher speeds of operation are possible, compared to the conventional image sensors using multi-bit analog to digital converters (ADCs). The frame rate of the proposed image sensor is over 2000 frames per second, which is higher than those of the conventional CMOS image sensors. The output signal of an active pixel sensor is applied to a comparator and compared with a reference level. The 1-bit output data of the binary process is determined by this level. To obtain a video signal, the 1-bit output data is stored in the memory and is read out by horizontal scanning. The proposed chip is composed of a GBT pixel array (144 x 100), binary-process circuit, vertical scanner, horizontal scanner, and readout circuit. The operation mode can be selected from between binary mode and multi-bit mode.

关键词： image sensor binary processing active pixel sensor gate/body-tied MOSFET photodetector

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