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Text Extraction and Recognition in Natural Scene Images using Contourlet Transform and PNN
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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Secondly, horizontal projection is applied on text regions for segmenting lines and vertical projection is applied on each text line for segmenting characters. ...
Particularly, in natural scene images, the text content provides explicit information to understand the semantics of images. ...
INTRODUCTION Huge quantities of textual data are present in the natural scene images and required to be automatically processed for text recognition in order to understand scene content. ...
doi:10.35940/ijitee.b1056.1292s19
fatcat:zsq7anpyb5csrogr3wqiihhql4
Recognition, segmentation and retrieval of gang graffiti images on a mobile device
2013
2013 IEEE International Conference on Technologies for Homeland Security (HST)
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The first method is color recognition based on touchscreen tracing, the second method is color image segmentation based on Gaussian thresholding and the third method is content based image retrieval. ...
Our experimental results show an image retrieval accuracy of 92.8% for gang graffiti scene recognition and an image retrieval accuracy of 50.0% for gang graffiti component classification. ...
Our content based image retrieval method is tested for accuracy and speed in two scenarios: scene recognition and gang graffiti component classification. ...
doi:10.1109/ths.2013.6698996
fatcat:wxeay2aiene4dce5t7aspx6j54
A SURVEY ON RECENT METHODOLOGIES IN MULTILINGUAL CHARACTER DETECTION AND RECOGNITION
2019
International Journal of Engineering Applied Sciences and Technology
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Content discovery and recognition has risen as a significant issue in the previous couple of years. ...
Headways in the field of computer vision, Artificial Intelligence and some constant applications dependent on content identification and recognition has taken more consideration of researchers. ...
Deep learning based region classification (DLRC) focuses on extracting hand crafted features and deep CNN based features for region classification. ...
doi:10.33564/ijeast.2019.v04i03.062
fatcat:6tswkhkmwbcfnne6tk6z2jm6jm
Scene Classification Using Bag-of-Regions Representations
2007
2007 IEEE Conference on Computer Vision and Pattern Recognition
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First, images are partitioned into regions using one-class classification and patch-based clustering algorithms where one-class classifiers model the regions with relatively uniform color and texture properties ...
Given these representations, scene classification is done using Bayesian classifiers. ...
of clusters based only on low-level features), retrieval (filtering images in archives based on content) and object recognition (the probability of an unknown object/region that exhibits several local ...
doi:10.1109/cvpr.2007.383375
dblp:conf/cvpr/GokalpA07
fatcat:kxb5oecqmngypeplj6acjm7epu
Video scene segmentation to separate script
2013
2013 3rd IEEE International Advance Computing Conference (IACC)
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In this system 91% of the Character gets recognized successfully using Texture-based approaches to automatic detection, segmentation and recognition of visual text occurrences in images and video frames ...
matching techniques are more sensitive to font and size variations of the characters than the feature classification methods. ...
Architecture of Video Scene Segmentation and Recognition
system
TABLE II . ...
doi:10.1109/iadcc.2013.6514410
fatcat:uqz66cunybeoladuxglw3o7bpa
Modeling of Remote Sensing Image Content Using Attributed Relational Graphs
[chapter]
2006
Lecture Notes in Computer Science
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First, scenes are decomposed into regions using pixel-based classifiers and an iterative split-and-merge algorithm. ...
Next, spatial relationships of regions are computed using boundary, distance and orientation information based on different region representations. ...
The segmentation approach we have used in this work consists of pixel-based classification and an iterative split-and-merge algorithm [9] . ...
doi:10.1007/11815921_52
fatcat:ntpnfhcq7nbgnbsd55v7vscowe
A MPEG-7 compliant Video Management System: BilVMS
2003
Digital Media Processing for Multimedia Interactive Services
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The scene decomposition is achieved using a HMM-based formulation by multimodal features. ...
The system is capable of temporally segmenting video into shots, as well as obtaining a semantically meaningful group of shots, i.e. scenes. ...
While, videotext recognition capability adds important information about the content to the database, the scene-based summarization is a versatile tool for better comprehensiveness of the summary. ...
doi:10.1142/9789812704337_0014
fatcat:6esdknldefgiljsdwtr375g72y
Object Recognition Based on the Context Aware Decision-Level Fusion in Multiviews Imagery
2015
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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In the single view process, defining region's properties for each of the segmented regions, the object-based image analysis (OBIA) is performed independently on the individual views. ...
In the second stage, the classified objects of all views are fused together through a decision-level fusion based on the scene contextual information in order to refine the classification results. ...
2 and Vaihingen datasets, respectively, used in this paper [27] , http://www.ifp.unistuttgart.de/dgpf/DKEP-Allg.html. ...
doi:10.1109/jstars.2014.2362103
fatcat:iicgvaheqjhybie4skrkzsoygi
A bag of words approach for semantic segmentation of monitored scenes
2016
2016 International Symposium on Signal, Image, Video and Communications (ISIVC)
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Then, the second step is based on SIFT keypoints and uses the bag of words representation of the regions for the classification. ...
Compared to existing techniques, our method provides more compact representations of scene contents and the segmentation result is more consistent with human perception due to the combination of the color ...
Segmenting and identifying the different regions in a monitored scene is a very useful preprocessing step for detecting and recognizing objects and events of interest. ...
doi:10.1109/isivc.2016.7893967
dblp:conf/isivc/BouachirTBB16
fatcat:bg4f2kg6hfa6renpg7e62oilo4
Content-Sensitive Multilevel Point Cluster Construction for ALS Point Cloud Classification
2019
Remote Sensing
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Two scenes are used to experimentally test the method, and it is compared with three other state-of-the-art techniques. ...
Thus, the segmentation results take the entity content (density distribution) into account, and the initial classification unit is adapted to the density of ground objects. ...
Conflicts of Interest: There is no conflict of interest. ...
doi:10.3390/rs11030342
fatcat:m7yjbgi7afcwlhhsvbunbxsyxa
A Bag of Words Approach for Semantic Segmentation of Monitored Scenes
[article]
2013
arXiv
pre-print
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Then, the second step is based on SIFT keypoints and uses the bag of words representation of the regions for the classification. ...
Compared to existing techniques, our method provides more compact representations of scene contents and the segmentation result is more consistent with human perception due to the combination of the color ...
Segmenting and identifying the different regions in a monitored scene is a very useful preprocessing step for detecting and recognizing objects and events of interest. ...
arXiv:1305.3189v1
fatcat:rhxgqma4kfdediw374su5huhhm
Segmented character recognition using curvature based global image feature
2019
Turkish Journal of Electrical Engineering and Computer Sciences
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The proposed feature is employed for segmented character recognition using Chars74k dataset and ICDAR 2003 character recognition dataset. ...
In this paper, a curvature-based global image feature and description for segmented character recognition is proposed. ...
Among various global features, region and contour-based shape features are used to describe image content. ...
doi:10.3906/elk-1806-195
fatcat:ha36efjrmzgqngrwlah6zuoaxi
Scene Semantic Recognition based on Modified Fuzzy C-Mean and Maximum Entropy using Object-to-Object Relations
2021
IEEE Access
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INDEX TERMS Scene recognition, object segmentation, recognition, bag of features, artificial neural network, maximum entropy, object pattern. ...
First, denoising and smoothing are applied on scene data. Second, modified Fuzzy C-Means integrates with super-pixels and Random Forest for the segmentation of objects. ...
Here, regions and locations of objects are defined through segmentation and these extracted regions are used for further classification tasks. ...
doi:10.1109/access.2021.3058986
fatcat:rtst7yrcvndqlmdpo7grxlwjia
Automatic Video Scene Segmentation to Separate Script and Recognition
[chapter]
2015
Advances in Intelligent Systems and Computing
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In this system 92.15% of the Character gets recognized successfully using Texture-based approaches to automatic detection, segmentation and recognition of visual text occurrences in images and video frames ...
The template matching techniques are more sensitive to font and size variations of the characters than the feature classification methods. ...
and content-based image/video indexing. ...
doi:10.1007/978-3-319-12012-6_25
fatcat:argtai5h5vhsdhfg6gztccfzgu
A DECISION LEVEL FUSION METHOD FOR OBJECT RECOGNITION USING MULTI-ANGULAR IMAGERY
2013
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Then, in the second stage, the initial classified regions of each individual multi-angular image are fused through a decision level fusion based on the definition of scene context. ...
In this paper, the capability of multi-angular satellite imagery is used in order to solve object recognition difficulties in complex urban areas based on decision level fusion of Object Based Image Analysis ...
: Calculating suitable structural features based on spatial characteristics and heights of segmented regions provide another part of internal context for using in the object classification process. ...
doi:10.5194/isprsarchives-xl-1-w3-409-2013
fatcat:3himvbkirbem3fzdrzmbd6mkpi
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