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Corn Leaf Diseases Diagnostic Techniques Based on image recognition

Corn Leaf Diseases Diagnostic Techniques Based on Image Reco...

引用

1st international conference on Communications and Information processing (ICCIP 2012)

作者： Zhu, Juan-hua Wu, Ang Li, Peng Henan Agr Univ Coll Mech & Elect Engn Zhengzhou 450002 Peoples R China

ISBN: (纸本)9783642319648

Corn leaf diseases are automatically recognized by digital image processing techniques and pattern recognition method. The method is separated into three steps. First, the gray-scale images are gotten from color images which were caught by numeral camera, which is enhanced by histogram equalization method, and the unwanted noise is removed from the image. Secondly, the disease spots were segmented from leaves based on the iterative threshold method and morphological methods. Finally, the shape characteristic parameters of disease spots, such as area, perimeter, rectangularity, circularity and shape complexity, are extracted, which are used to identify and diagnose diseases. The results show that the corn leaf diseases of the 30 images could be well diagnosed with a diagnostic rate of 80%.

关键词： Corn Leaf Spots Diseases Diagnostic image recognition Feature Extraction

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A new problem in face image analysis: Finding kinship clues for siblings pairs

A new problem in face image analysis: Finding kinship clues ...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Bottino, A. De Simone, M. Laurentini, A. Vieira, T. Computer Graphics and Vision Group Politecnico di Torino C.so Duca degli Abruzzi 24 Torino Italy Departamento de Eletrônica e Sistemas Universidade Federal de Pernambuco Recife Brazil

ISBN: (纸本)9789898425980

Human face conveys to other human beings, and potentially to computers, much information such as identity, emotional states, intentions, age and attractiveness. Among this information there are kinship clues. Face kinship signals, as well as the human capabilities of capturing them, are studied by psychologist and sociologists. In this paper we present a new research aimed at analyzing, with image processing/pattern analysis techniques, facial images for detecting objective elements of similarity between siblings. To this end, we have constructed a database of high quality pictures of pairs of siblings, shot in controlled conditions, including frontal, profile, expressionless and smiling face images. A first analysis of the database has been performed using a commercial identity recognition software. Then, for discriminating siblings, we combined eigenfaces, SVM and a feature selection algorithm, obtaining a recognition accuracy close to that of a human rating panel.

关键词： Principal component analysis

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Dictionary based hyperspectral image retrieval

Dictionary based hyperspectral image retrieval

引用

1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Veganzones, Miguel A. Datcu, Mihai Graña, Manuel Grupo de Inteligencia Computacional Universidad del País Vasco Bilbao Spain Wessling Germany

ISBN: (纸本)9789898425980

The normalized information distance (NID) is an universal metric distance based on Kolmogorov complexity. However, NID is not computable in a Turing sense. The normalized compression distance (NCD) is a computable distance that approximates NID by using normal compressors. NCD is a parameter-free distance that compares two signals by their lengths after separate compression relative to the length of the signal resulting from their concatenation after compression. The use of NCD for image retrieval over large image databases is difficult due to the computational cost of compressing the query image concatenated with every image in the database. The use of dictionaries extracted by dictionary-based compressors, such as the LZW compression algorithm, has been proposed to overcome this problem. Here we propose a Content-Based image Retrieval system based on such dictionaries for the mining of hyperspectral databases. We compare results using the Normalized Dictionary Distance (NDD) and the Fast Dictionary Distance (FDD) against the NCD over different datasets of hyperspectral images. Results validate the applicability of dictionaries for hyperspectral image retrieval.

关键词： Query processing

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Icounter: Development of an optical readout method for mechanical counters

Icounter: Development of an optical readout method for mecha...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Benyoucef, Dirk Held, Pirmin Bier, Thomas Digital Communications and Signal Processing Lab Furtwangen University Robert-Gerwig-Platz 1 78120 Furtwangen Germany

ISBN: (纸本)9789898425980

Mechanical counters are still very common in electricity, water and gas meters. Automatic readout of the dial count without modifying the mechanics of the counter is only possible using expensive image processing methods. Therefore the topic of this report is a new method for automatically reading out the counter values without the need of additional mechanical or parallel electronic parts inside the counter. Instead the different reflection properties of the different digits are measured and evaluated. This is done using only simple electronic parts and a microcontroller. In the first part of the paper the hardware for measuring the reflection values is presented. A model of this hardware with special emphasis on the influences of the environment is discussed in the next part. Following this, two classification methods, for distinguishing the digits are analyzed. For showing the properties of the new readout system measurements and simulations are given in the end.

关键词： Cluster analysis

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3D bending of surfaces and volumeswith an application to brain torque modeling

3D bending of surfaces and volumeswith an application to bra...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Pepe, Antonietta Tohka, Jussi Department of Signal Processing Tampere University of Technology P.O. Box 553 Tampere FIN-33101 Finland

ISBN: (纸本)9789898425980

In this work, we propose a novel space deformation model for local bending of 3D volumes and surfaces. The model can be easily controlled through accommodation of a few intuitive parameters. Experiments on volumes, parametric surfaces, and polygonal surfaces show that our method has increased modeling capabilities when compared to the previous space deformation methods for local bending. We apply this new, more flexible model for space bending to model human brain asymmetry. In particular, we develop an image processing pipeline for automatic generation of a set of realistic 3D brain magnetic resonance (MR) images for which the asymmetry is known. This dataset can be used for the quantitative validation of voxel and surface based methods for studying brain shape asymmetry. The pipeline encompasses a realistic modeling of the anatomical rightward bending of the inter-hemispheric fissure in human brain.

关键词： Magnetic resonance imaging

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Fast template matching of repetitive objects in stereoscopy

Fast template matching of repetitive objects in stereoscopy

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Nehmadi, Youval Kalantyrsky, Orly Guterman, Hugo Department of Electrical and Computer Engineering Ben-Gurion University of Negev Beer-Sheva Israel Department of Computer Science Tel Aviv-Yaffo Academic College Tel Aviv Israel

ISBN: (纸本)9789898425980

One of the challenges of stereovision is to process images with repetitive objects. In order to calculate the distance to an object, matching of the corresponding points between two images must be done. When repetitive objects exist, matching is not straightforward. Many known stereo methods rely on a uniqueness constraint. A uniqueness constraint assumes that only one correct match exists between stereo images. Some algorithms ignore repetitive objects and omit them in the depth map. We present a method that does not employ a uniqueness constraint, but rather determines whether an object is repetitive and then solves the matching problem by finding a unique object that is in close proximity to the object.

关键词： stereo image processing

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IRIS recognition in visible light domain

IRIS recognition in visible light domain

引用

1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Riccio, Daniel De Marsico, Maria Biometric and Image Processing Laboratory University of Salerno via Ponte don Melillo 84084 Fisciano Italy Dipartimento di Informatica Sapienza Università di Roma via Salaria 113 00198 Rome Italy

ISBN: (纸本)9789898425980

Present iris recognition techniques allow very high recognition performances in controlled settings and with cooperating users;this makes iris a real competitor to other biometric traits like fingerprints, with the further advantage of requiring a contactless acquisition. Moreover, most of the existing approaches are designed for Near Infrared or Hyperspectral images, which are less affected by changes in illumination conditions. Current research is focusing on designing new techniques aiming to ensure high accuracy even on images acquired in visible light and in adverse conditions. This paper deals with an approach to iris matching based on the combination of local features: Linear Binary patterns (LBP) and discriminable textons (BLOBs). Both these technique have been readapted in order to deal with images captured in variable visible light conditions, and affected by noise due to distance/resolution or to scarce user collaboration (blurring, off-axis iris, occlusion by eyelashes and eyelids). The obtained results are quite convincing and strongly motivate the addition of more local features.

关键词： Biometrics

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Layout Analysis for Arabic Historical Document images Using machine learning

Layout Analysis for Arabic Historical Document Images Using ...

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13th international conference on Frontiers in Handwriting recognition (ICFHR)

作者： Bukhari, Syed Saqib Breuel, Thomas M. Asi, Abedelkadir El-Sana, Jihad Tech Univ Kaiserslautern Kaiserslautern Germany Ben Gurion Univ Negev Negev Israel

ISBN: (纸本)9780769547749;9781467322621

Page layout analysis is a fundamental step of any document image understanding system. We introduce an approach that segments text appearing in page margins (a.k.a side-notes text) from manuscripts with complex layout format. Simple and discriminative features are extracted in a connected-component level and subsequently robust feature vectors are generated. Multi-layer perception classifier is exploited to classify connected components to the relevant class of text. A voting scheme is then applied to refine the resulting segmentation and produce the final classification. In contrast to state-of-the-art segmentation approaches, this method is independent of block segmentation, as well as pixel level analysis. The proposed method has been trained and tested on a dataset that contains a variety of complex side-notes layout formats, achieving a segmentation accuracy of about 95%.

关键词： document image processing feature extraction image classification image segmentation learning (artificial intelligence) natural languages text analysis

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The research on the monitoring system for conveyor belt based on pattern recognition

The research on the monitoring system for conveyor belt base...

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1st international conference on Intelligent System and Applied Material (GSAM 2012)

作者： Wang ChuanQi Zhang Jian HEBEI United Univ Sch Informat Engn Tangshan City Hebei Peoples R China

ISBN: (纸本)9783037853689

Currently, the measures for monitoring the conveyor belt from tearing are all in contact-type, therefore, the recognition would only be valid while the leakage of material occured or the belt dropt, since the belt has been torn with a certain length. Then, at that time, the economic losses would be caused. Furthermore, the related devices for monitoring belt would cause abrasion due to contact friction, which is harmful for belt. In this research, a contactless monitoring method based on image processing and pattern recognition would be discussed, which is able to provide an effecient way to monitor conveyor belt in real time and with non-blind area. While the tearing occurs, the system enables to generate the signal for shutting off, then to protect the belt maximumly.

关键词： conveyor belt tearing pattern recognitoin threshold segmentation least square method fitted curve

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Clustering complex multimedia objects using an ensemble approach

Clustering complex multimedia objects using an ensemble appr...

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1st international conference on pattern recognition Applications and Methods, ICPRAM 2012

作者： Oviedo, Ana Isabel Ortega, Oscar Computer Department Universidad Pontificia Bolivariana Medellin Colombia System Engineering Department Universidad de Antioquia Medellin Colombia

ISBN: (纸本)9789898425980

A complex multimedia object is an information unit composed by multiple media types like text, images, audio and video. Applications related with huge sets of such objects exceed the human capacity to synthesize useful information. The search for similarities and dissimilarities among objects is a task that has been done through clustering analysis, which tries to find groups in unlabeled data sets. Such analysis applied to complex multimedia object sets has a special restriction. The method must analyze the multiple media types present in the objects. This paper proposes a clustering ensemble that jointly assesses several media types present in this kind of objects. The proposed ensemble was applied to cluster webpages, constructing a text and image clustering prototypes. The Hubert's statistic was used to evaluate the ensemble performance, showing that the proposed method creates clustering structures more similar to the real classification than a joint-feature vector.

关键词： Clustering Complex multimedia objects Ensemble methods Unsupervised learning

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