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检索条件"任意字段=Conference on Image Processing and Pattern Recognition in Remote Sensing"

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image classification approach for automatic identification of grassland weeds

Image classification approach for automatic identification o...

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conference on remote sensing and Modeling of Ecosystems for Sustainability III

作者： Gebhardt, Steffen Kuehbauch, Walter Univ Bonn Inst Crop Sci & Resouce Conservat Bonn Germany

ISBN: (纸本)0819463779

The potential of digital image processing for weed mapping in arable crops has widely been investigated in the last decades. In grassland farming these techniques are rarely applied so far. The project presented here focuses on the automatic identification of one of the most invasive and persistent grassland weed species, the broad-leaved dock (Rumex obtusifolius L.) in complex mixtures of grass and herbs. A total of 108 RGB-images were acquired in near range from a field experiment under constant illumination conditions using a commercial digital camera. The objects of interest were separated from the background by transforming the 24 bit RGB-images into 8 bit intensities and then calculating the local homogeneity images. These images were binarised by applying a dynamic grey value threshold. Finally, morphological opening was applied to the binary images. The remaining contiguous regions were considered to be objects. In order to classify these objects into 3 different weed species, a soil and a residue class, a total of 17 object-features related to shape, color and texture of the weeds were extracted. Using MANOVA, 12 of them were identified which contribute to classification. Maximum-likelihood classification was conducted to discriminate the weed species. The total classification rate across all classes ranged from 76 % to 83 %. The classification of Rumex obtusifolius achieved detection rates between 85 % and 93 % by misclassifications below 10 %. Further, Rumex obtusifolius distribution and the density maps were generated based on classification results and transformation of image coordinates into Gau beta-Kruger system. These promising results show the high potential of image analysis for weed mapping in grassland and the implementation of site-specific herbicide spraying.

关键词： automatic weed mapping precision farming image processing pattern recognition

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Towards content based object recognition with image primitive

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conference on image processing - Algorithms and Systems, Neural Networks, and Machine Learning

作者： Wang, Guisong Kinser, Jason George Mason Univ Sch Computat Sci Fairfax VA 22030 USA

ISBN: (纸本)0819461040

Content-based object recognition is very useful in many applications, such as medical image processing and diagnosis, target identification with satellite remote sensing. For content-based object recognition, the representation of image segments is critical. Although there are already some approaches to represent image shapes, many of them have limitations because of their insensitivity to the deviations of object appearance. In this paper, an approach is proposed by constructing an image primitive database and representing image with a basis set extracted from the database. The cortical modeling is used here to extract the basis set by isolating the inherent shapes within each image from an image database and defines shapes from this basis set. In our approach, image segments are clustered based on similarity in perimeter and size instead of centroid based metrics by employing the fractional power filter, and the clusters are represented in descriptive vectors as signatures and form basis for shape representation. This approach has advantages in sensitivity to the idiosyncratic nature of the distribution of shapes and efficiency. For validation, we selected a large number of images from web sites randomly. The experiments indicate that describing shapes from this basis set is robust to alterations of the shape such as small occlusions, limited skew, and limited range.

关键词： object recognition image primitives segmentation clustering shape representation neural networks

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Recent results of Integrated sensing and processing using a programmable hyperspectral imaging sensor.

Recent results of Integrated Sensing and Processing using a ...

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conference on Optical pattern recognition XVII

作者： Muise, Robert Mahalanobis, Abhijit MFC Lockheed Martin 5600 Sand Lake Rd Orlando FL 32819 USA

ISBN: (纸本)0819463019

In this paper we present an information sensing system which integrates sensing and processing resulting in the direct collection of data which is relevant to the application. Broadly, integrated sensing and processing (ISP) considers algorithms that are integrated with the collection of data. That is, traditional sensor development tries to come up with the "best" sensor in terms of SNR, resolution, data rates, integration time, etc... and traditional algorithm development tasks might wish to optimize probability of detection, false alarm rate, class separability, etc... For a typical Automatic Target recognition (ATR) problem, the goal of ISP is to field algorithms which "tell" the sensor what kind of data to collect next and the sensor alters its parameters to collect the "best" information in order that the algorithm performs optimally. We demonstrate an ISP system which utilizes a near Infrared (NIR) Hadamard multiplexing imaging sensor. This prototype sensor incorporates a digital mirror array (DMA) device in order to realize a Hadamard multiplexed imaging system. Specific Hadamard codes can be sent to the sensor to realize inner products of the underlying scene rather than the scene itself The developed ISP algorithm uses an ATR metric to send codes to the sensor in order to collect only the information 'relevant to the ATR problem. The result is a multiple resolution hyperspectral cube with full resolution where targets are present and less than full resolution where there are no targets. Essentially, this is compressed sensing.

关键词： Sensors Multiplexing Imaging systems Algorithm development Automatic target recognition Compressed sensing Hyperspectral imaging Mirrors Detector arrays image resolution

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Evaluation of different fitness functions integrated with genetic algorithm on unsupervised classification of satellite images

Evaluation of different fitness functions integrated with ge...

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image and Signal processing for remote sensing XII

作者： Yang, Y.F. Yanga, M.D. Tsaia, T.Y. Civil Engineering National Chung Hsing University Kuokuang Road Taichung county 250 402 Taiwan

ISBN: (纸本)0819464600

In traditional unsupervised classification method, the number of clusters usually needs to be assigned subjectively by analysts, but in fact, in most situations, the prior knowledge of the research subject is difficult to acquire, so the suitable and best cluster numbers are very difficult to define. Therefore, in this research, an effective heuristic unsupervised classification method - Genetic Algorithm (GA) is introduced and tested here, because it can be through the mathematical model and calculating procedure of optimization to determine the best cluster numbers and centers automatically. Furthermore, two well-known models-Davies-Bouldin's and the K-Means algorithm, which adopted by most research for the applications in pattern classification, are integrated with GA as the fitness functions. In a word, in this research, a heuristic method - Genetic Algorithm (GA), is adopted and integrated with two different indices as the fitness functions to automatically interpret the clusters of satellite images for unsupervised classification. The classification results were compared to conventional ISODATA results, and to ground truth information derived from a topographic map for the estimation of classification accuracy. All image-processing program is developed in MATLAB, and the GA unsupervised classifier is tested on several image examples.

关键词： pattern recognition

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A hardware implementation of the discrete Pascal transform for image processing

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conference on image processing - Algorithms and Systems, Neural Networks, and Machine Learning

作者： Goodman, Thomas J. Aburdene, Maurice F. Bucknell Univ Dept Elect Engn Lewisburg PA 17837 USA

ISBN: (纸本)0819461040

The discrete Pascal transform is a polynomial transform with applications in pattern recognition, digital filtering, and digital image processing. It already has been shown that the Pascal transform matrix can be decomposed into a product of binary matrices. Such a factorization leads to a fast and efficient hardware implementation without the use of multipliers, which consume large amounts of hardware. We recently developed a field-programmable gate array (FPGA) implementation to compute the Pascal transform. Our goal was to demonstrate the computational efficiency of the transform while keeping hardware requirements at a minimum. images are uploaded into memory from a remote computer prior to processing, and the transform coefficients can be offloaded from the FPGA board for analysis. Design techniques like as-soon-as-possible scheduling and adder sharing allowed us to develop a fast and efficient system. An eight-point, one-dimensional transform completes in 13 clock cycles and requires only four adders. An 8x8 two-dimensional transform completes in 240 cycles and requires only a top-level controller in addition to the one-dimensional transform hardware. Finally, through minor modifications to the controller, the transform operations can be pipelined to achieve 100% utilization of the four adders, allowing one eight-point transform to complete every seven clock cycles.

关键词： Field programmable gate arrays Clocks image processing Edge detection Binary data image filtering Matrices Digital filtering Digital image processing pattern recognition

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Synchronous image acquisition based on network synchronization

Synchronous image acquisition based on network synchronizati...

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2006 conference on Computer Vision and pattern recognition Workshops

作者： Litos, Georgios Zabulis, Xenophon Triantafyllidis, Georgios Informatics and Telematics Institute Thessaloniki Greece

ISBN: (纸本)0769526462

In this paper, a software-based system for the real-time synchronization of images captured by a low-cost camera framework is presented. It is most well suited for cases where special hardware cannot be utilized (e.g. remote or wireless applications) and when cost efficiency is critical. The proposed method utilizes messages to establish a consensus on the time of image acquisition and NTP synchronization of computer clocks. It also provides with an error signal, in case of failure of the synchronization. The evaluation of the proposed algorithm using a precise LED array system (1ms accuracy) proves the effectiveness of this method. © 2006 IEEE.

关键词： image processing

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Anon-parametric classification strategy for remotely sensed images using both spectral and textural information

Anon-parametric classification strategy for remotely sensed ...

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3rd IASTED International conference on Signal processing, pattern recognition, and Applications

作者： Kumar, Mukesh Miller, Douglas A. Dept. of Civil and Environmental Engineering Pennsylvania State University United States EMS Environment Institute Pennsylvania State University United States

ISBN: (纸本)0889865477

A classification strategy which does not require a priori assumptions about the statistical distribution of training pixels in each class is proposed. This method uses an indicator kriging approach in feature space to classify remotely sensed images incorporating both spectral and textural information of bands. Texture information is used only in cases where spectral information is not sufficient to resolve the assignment of the pixel to a class. Application of the proposed methodology on a remotely sensed natural scene shows an improvement in the overall classification accuracy with respect to the case when the scenes are classified by the traditional supervised Gaussian maximum likelihood classification (GMLC) method using either spectral band only or using both spectral and textural bands. A marked improvement in classification accuracy is obtained particularly for the classes for which the GMLC's assumption of multivariate normal distribution of training pixels in a class fails miserably.

关键词： remote sensing

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Application of passive imaging polarimetry in the discrimination and detection of different color targets of identical shapes using color-blind imaging sensors

Application of passive imaging polarimetry in the discrimina...

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conference on Polarization - Measure, Analysis and remote sensing VII

作者： El-Saba, A. M. Alam, M. S. Surpanani, A. Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

ISBN: (纸本)0819462969

Important aspects of automatic pattern recognition systems are their ability to efficiently discriminate and detect proper targets with low false alarms. In this paper we extend the applications of passive imaging polarimetry to effectively discriminate and detect different color targets of identical shapes using color-blind imaging sensor. For this case of study we demonstrate that traditional color-blind polarization-insensitive imaging sensors that rely only on the spatial distribution of targets suffer from high false detection rates, especially in scenarios where multiple identical shape targets are present. On the other hand we show that color-blind polarization-sensitive imaging sensors can successfully and efficiently discriminate and detect true targets based on their color only. We highlight the main advantages of using our proposed polarization-encoded imaging sensor.

关键词： passive imaging Stokes imaging polarimetry polarization-encoding optical processing target recognition

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Digital image processing of high resolution aerial photograph of Shallow Marine Sanctuary, Victoria, Australia

Digital image processing of high resolution aerial photograp...

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2006 International conference on Advances in Space Technologies, ICAST

作者： Saeed, Fawad

ISBN: (纸本)1424405149

In this paper the potential of remote sensing as a tool to study Marine Sanctuary has been explored. There are two main methods that can be used to extract information from the aerial photograph / satellite imagery;visual interpretation and digital image processing. Visual interpretation takes advantage of the human skills to recognize data "content" by combining several elements of image interpretation. It relies on experience, a prior knowledge and skilled analysts qualities to produce excellent results. Alternatively, digital image classification employs computer techniques which are mostly based on the reflection values of individual pixels and use statistical pattern recognition methods. In the current study, the main area of interest was distribution of sand, rocky reef, rocky rubble and sea grass in the sanctuary. The study showed that the supervised classification approach was a superior technique to employ for such studies as compare to other traditional approaches. Here, the higher degree of interaction between the analyst and the machine complements the limitations of each other. Furthermore, the analyst is also given the opportunity to "control" which digital signatures best qualify to represent a certain resource class considering the fact that the analyst has access to ground truth data to fine tune the classification. © 2006 IEEE.

关键词： Antennas

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Tropospheric aerosols remote sensing over the water surface of Penang Island

Tropospheric aerosols remote sensing over the water surface ...

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conference on Signal processing, Sensor Fusion, and Target recognition XV

作者： Hashim, S. A. MatJafri, M. Z. Abdullah, K. Lim, H. S. Wong, C. J. Salleh, N. Mohd. Univ Sains Malaysia Sch Phys Minden 11800 Pulau Pinang Malaysia

ISBN: (纸本)0819462918

Tropospheric aerosols play an important role in climate change. Aerosols are typically studied over deep clear water, due to the relatively constant reflectance of water and the ability to easily separate surface and atmospheric contributions on the satellite signal. A methodology based on multi-spectral approach was employed to map tropospheric aerosols concentrations over the water areas surrounding Penang Island. The aim of this study was to estimate the pollutants concentrations using remote sensing techniques. In this study, we attempted to derive AOT(Aerosol Optical Thickness) values from the sky transmittance measurements in the visible spectrum. The transmittance values were measured at the sea surface using a handheld spectroradiometer. The correspond PM10 readings were taken simultaneously during the transmittance measurements acquisition of the imageries using a Dust Trak(TM) meter. The PCI Geomatica version 9.1 digital image processing software was used in all image-processing analyses. The results produced a linear relationship between PM10 and AOT values over the water surface of Penang Island. Finally, The PM10 concentration map over the water surface of Penang Island was generated using Kriging interpolation technique. This study has indicated the potential use of a handheld spectroradiometer for air quality study.

关键词： tropospheric AOT transmittance PM10 spectroradiometer DustTrak (TM) meter

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