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检索条件"任意字段=6th Indian Conference on Computer Vision, Graphics and Image Processing"

共 2011 条记录，以下是511-520 订阅

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A new approach for image thresholding under uneven lighting conditions

A new approach for image thresholding under uneven lighting ...

引用

6th IEEE/ACIS International conference on computer and Information Science in Conjunction with 1st IEEE/ACIS International Workshop on e-Activity

作者： Tsai, Yao-Hong Hsuan Chuang Univ Dept Comp Sci Hsinchu 300 Taiwan

ISBN: (纸本)9780769528410

image thresholding is a useful method in many image processing and computer vision applications. However, it is not always satisfactory in all applications because of non-uniform illuminations. Otsu's method has been widely used as the classical technique in real thresholding tasks. In this paper, we propose a novel method for adaptive local thresholding by applying Otsu's results. Based on simulated annealing, the proposed algorithm searches the optimal threshold for each partitioned subimage according to the quadtree data structure. It is also scale invariant for different object sizes. For reducing the computations, an improvement of Otsu's method is also developed. Experimental results show the efficiency of the proposed method.

关键词： Simulated annealing

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Anomaly Detection using Context Dependent Optical Flow 11

Anomaly Detection using Context Dependent Optical Flow

引用

11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Mondal, Ranjan Chanda, Bhabatosh Indian Stat Inst Kolkata India

ISBN: (纸本)9781450366151

Anomaly detection is a major task in crowd management through video surveillance. It refers to the events which are deviated from normal events. We have introduced an unsupervised method to detect motion anomaly in surveillance video. In this work we have considered only optical flow as feature. First, for each frame we compute magnitude of optical flow of motion using flownet2 [10]. then, mean of magnitude of flow due to regular normal motion (given in training data) is computed at each pixel where such motion exists in the training video frames. Our strategy is to compare the motion under consideration against this mean flow magnitude, and we expect that the anomalous motion would differ significantly from normal motion. An autoencoder type network is trained to detect this anomaly. Training data patch is constructed by Interleaving the columns of mean optical flow patch and the corresponding flow patch from each frame. this interleaving is done to incorporate context dependency. the autoencoder is trained to minimize mean-square reconstruction error between input column wise interleaved patch and output (i.e., reconstructed patch) of the autoencoder. During testing, a patch is declared anomalous if the reconstruction error is high compared to the training error. Experiments have been carried out on UCSD and UMN dataset and are compared with other methods. Our method gives comparable results with other state-of-the-art methods.

关键词： Anomaly Detection Motion Representation Activity Recognition Unsupervised Method

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Pattern Recognition and Machine Intelligence 2011

引用

丛书名： Lecture Notes in computer Science

2011年

作者： Sergei O. Kuznetsov Deba P. Mandal Malay K. Kundu Sankar Kumar Pal

ISBN: (数字)9783642217869

ISBN: (纸本)9783642217852

this book constitutes the refereed proceedings of the 4th International conference on Pattern Recognition and Machine Intelligence, PReMI 2011, held in Moscow, Russia in June/July 2011. the 65 revised papers presented together with 5 invited talks were carefully reviewed and selected from 140 submissions. the papers are organized in topical sections on pattern recognition and machine learning; image analysis; image and video information retrieval; natural language processing and text and data mining; watermarking, steganography and biometrics; soft computing and applications; clustering and network analysis; bio and chemo analysis; and document image processing.

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Deep Learning approaches for image Dehazing 6

Deep Learning approaches for Image Dehazing

引用

6th International conference and Workshops on Recent Advances and Innovations in Engineering (ICRAIE)

作者： Pavethra, M. Umadevi, M. SRM Inst Sci & Technol Dept Comp Technol Chennai Tamil Nadu India

ISBN: (纸本)9781665434027

computer visibility is a multi-sectoral systematic field concerned with how computers assist to improve high-level understanding of digital images and videos. Haze is an atmospheric natural phenomenon that hinders computer vision tasks. In the present era, image degradation is a major issue, and creating a high-quality, haze-free image remains a difficult challenge. As a consequence, the performance of many multimedia processing systems leads to poor object recognition and tracking. More haze removal algorithms have been proposed to counter this issue, which aesthetically enhances the visibility of visuals that have been deteriorated by adverse weather, hence eradicating the haze effect. Since haze is reliant on an uncertain scene depth, it is a significant challenge to resolve. this study investigated existing strategies for eradicating haze from obtained photographs. this review is designed to formulate strategies for researchers to point the appropriate direction for future advancements based on current accomplishments.

关键词： Single image Dehazing Multiple image Dehazing Atmospheric Scattering Model DCP Deep Learning

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IDA-UIE: An Iterative Framework for Deep Network based Degradation Aware Underwater image Enhancement 24

IDA-UIE: An Iterative Framework for Deep Network based Degra...

引用

15th indian conference on computer vision graphics and image processing

作者： Singh, Pranjali Guha, Prithwijit Indian Inst Technol Guwahati Ctr Intelligent Cyber Phys Syst Gauhati Assam India Indian Inst Technol Guwahati Dept Elect & Elect Engn Gauhati Assam India

ISBN: (纸本)9798400710759

Underwater image quality is often compromised due to factors like fluorescence, low illumination, absorption, and scattering. Recent advancements in underwater image enhancement have introduced various deep network architectures to address these issues. Typically, these methods employ a single network to tackle all degradation challenges. However, we hypothesize that deep networks trained for specific conditions outperform those trained for multiple degradation cases. Consequently, we propose an iterative framework that individually identifies and resolves a dominant degradation condition. We focus on eight specific degradation conditions: low illumination, low contrast, haziness, blurriness, noise, and color imbalances across three channels. Our approach involves designing a deep network capable of detecting the dominant degradation condition and selecting an appropriate deep network tailored for that specific condition. We further propose that our work is the creation of condition-specific datasets derived from high-quality images in two standard datasets, UIEB and EUVP. these datasets facilitate the training of enhancement networks specific to each degradation condition. Our proposed method performs better than the nine baseline methods on both UIEB and EUVP datasets.

关键词： Underwater Imaging Model Deep Learning Underwater image Enhancement

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Automatic segmentation and classification of pipeline images using mathematic morphology and fuzzy k-means algorithm

Automatic segmentation and classification of pipeline images...

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Iranian conference on Machine vision and image processing

作者： Ziashahabi, M. Sadjedi, H. Khezripour, H. Department of Engineering Shahed University Tehran Iran Department of Computer Engineering Amir-Kabir Univ. Tehran Iran

ISBN: (纸本)9781424497065

Defects on the Pipeline surface such as cracks cause main problems for governments, specifically when the pipeline is covered under the ground. Manual examination for surface defects in the pipeline has several disadvantages, including varying standards, and high cost. In this paper, a combination of two algorithms based on mathematical morphology and curvature evaluation for segmentation of defects is proposed. then, we use fuzzy k-means clustering to classify pipe defects. the proposed method can be completely automated and has been tested on more than 250 scanned images of petroleum pipelines of Iran. © 2010 IEEE.

关键词： Mathematical morphology

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Workflow for development and testing of an embedded vision application

Workflow for development and testing of an embedded vision a...

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6th IASTED International conference on Visualization, Imaging, and image processing, VIIP 2006

作者： Hemetsberger, H. Kogler, J. Humenberger, M. Zinner, C. Kubinger, W. Borbély, S. Dependable Embedded Control Systems Group ARC Seibersdorf Research GmbH Donau-City- Str. 1 1220 Vienna Austria

ISBN: (纸本)0889865981

Developing computer vision applications is a challenging task. Realizing such an application as an embedded system is even more difficult, due to the limited resources of the target platform. In this paper the methods for the realization of such an embedded vision application are introduced. this includes a description of a workflow that supports the development of an embedded vision system. Also, the tools used for development and testing of this application are presented. For each step in the development process either off-the-shelf or self-developed tools were deployed. the embedded system, a stereo vision sensor, was part of an autonomous vehicle which participated in the DARPA Grand Challenge 2005. this system was used for obstacle and lane detection in this competition.

关键词： computer vision

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Multiple Kernel Fisher Discriminant Metric Learning for Person Re-identification 11

Multiple Kernel Fisher Discriminant Metric Learning for Pers...

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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Ali, T. M. Feroz Velmurugan, Rajbabu Patel, Kalpesh K. Chaudhuri, Subhasis Indian Inst Technol Dept Elect Engn Mumbai Maharashtra India

ISBN: (纸本)9781450366151

Person re-identification addresses the problem of matching pedestrian images across disjoint camera views. Design of feature descriptor and distance metric learning are the two fundamental tasks in person re-identification. In this paper, we propose a metric learning framework for person re-identification, where the discriminative metric space is learned using Kernel Fisher Discriminant Analysis (KFDA), to simultaneously maximize the inter-class variance as well as minimize the intra-class variance. We derive a Mahalanobis metric induced by KFDA and argue that KFDA is efficient to be applied for metric learning in person re-identification. We also show how the efficiency of KFDA in metric learning can be further enhanced for person re-identification by using two simple yet efficient multiple kernel learning methods. We conduct extensive experiments on three benchmark datasets for person re-identification and demonstrate that the proposed approaches have competitive performance with state-of-the-art methods.

关键词： Person Re-identification Metric Learning Kernel Fisher Discriminant Analysis Multiple Kernel Fisher Discriminant Analysis

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computer-aided detection of proliferative cells and mitosis index in immunohistichemically images of meningioma

Computer-aided detection of proliferative cells and mitosis ...

引用

Iranian conference on Machine vision and image processing

作者： Anari, Vahid Mahzouni, Parvin Amirfattahi, Rasoul Islamic Azad University Khoramabad Branch Iran Isfehan University of Medical Science Isfahan Iran Department of Electrical and Computer Engineering Isfehan University Technology Iran

ISBN: (纸本)9781424497065

Immuonohistochemically images of meningioma which are stained by ki67 marker contain positive and negative cells. Accurate counting the number of positive and negative cells in such images play a critical role in diagnosing diffrent type of meningioma cancer. Since pathological images of meningioma contain complex cell cluster accurate cell counting methodology is a major challenge for pathologist physicians. In this paper we provide a computer aided algorithm for detecting proliferative cells and mitosis index in immunohistochemically images of meningioma. In the first stage of the algorithm fuzzy c-means clustering was used to extract positive and negative cells based on CIElab color space. In the second stage, ultraerosion operation was applied to count the number of individual and overlapped cells. Experimental result show that the proposed algorithm is able to overcome some disadvantage of traditional approaches with acceptable accuracy by pathologist physicians. © 2010 IEEE.

关键词： Color

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Conceptual Measurement Of Individual Pitches During the Stent Production 17

Conceptual Measurement Of Individual Pitches During The Sten...

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17th International conference on Interfaces and Human computer Interaction 2023, IHCI 2023, the 17th International conference on computer graphics, Visualization, computer vision and image processing 2023, CGVCVIP 2023 and 16th International conference on Game and Entertainment Technologies 2023, GET 2023

作者： Haas, Benedikt Sax, Eric Karlsruhe Germany

ISBN: (纸本)9789898704498

Due to cardiovascular diseases being the main cause of death in Germany in 2020, about 298,557 stents, which can be used to treat these kinds of diseases, were implanted. Stents are medical devices and therefore, need to fulfill corresponding requirements. the requirements, like the geometric form, have to be checked. In practice, in the case of maypole braided stents, this will be performed manually. In order to be more cost-efficient, an automatic visual inspection system is desirable. the proposed concept, representing such a system, consists of six steps: 1) image preprocessing, 2) mandrel detection, 3) dynamic image cropping, 4) pitch measurement, 5) pitch localization, and 6) modeling. Additionally, it allows to measure individual segments of the stent, enabling a precise error localization. Furthermore, the algorithm is designed to be executed during production. Lastly, the industrial environment, as well as requirements, are incorporated, such that an existing product diversity is not restricted. © 2023 Proceedings of the International conferences on Interfaces and Human computer Interaction 2023, IHCI 2023;computer graphics, Visualization, computer vision and image processing 2023, CGVCVIP 2023;and Game and Entertainment Technologies 2023, GET 2023. All rights reserved.

关键词： computer vision

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