A robust and geometric invariant digital image watermarking scheme based on robust feature points detector and local Zernike transform is proposed in this paper. The robust feature points detector is proposed based on SIFT algorithm to extract circular patches. A local Zernike moments-based watermarking scheme is raised. Each extracted circular patch is decomposed into a collection of binary patches and Zernike transform is applied to the appointed binary patches. Experimental results show that the proposed scheme is very robust against geometric distortions and common signal processing.
{"title":"A Geometric Invariant Digital Image Watermarking Scheme Based on Robust Feature Detector and Local Zernike Moments","authors":"Xiaochen Yuan, Chi-Man Pun","doi":"10.1109/CGIV.2012.17","DOIUrl":"https://doi.org/10.1109/CGIV.2012.17","url":null,"abstract":"A robust and geometric invariant digital image watermarking scheme based on robust feature points detector and local Zernike transform is proposed in this paper. The robust feature points detector is proposed based on SIFT algorithm to extract circular patches. A local Zernike moments-based watermarking scheme is raised. Each extracted circular patch is decomposed into a collection of binary patches and Zernike transform is applied to the appointed binary patches. Experimental results show that the proposed scheme is very robust against geometric distortions and common signal processing.","PeriodicalId":365897,"journal":{"name":"2012 Ninth International Conference on Computer Graphics, Imaging and Visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115672713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a Bezier curve is construct to represent a hand-drawn image, expressed in the forms of a set of consecutive dots. Using input's sampling points, an online handwritten curve is converted into a vectored curve by Newton-Lagrange interpolation. Although Newton-Lagrange curve can be used well in the approximation of the handwritten curve, their polynomials are not appropriate in the applications of computer aided geometric design (CAGD). Therefore, Newton-Lagrange curve will then be converted into a corresponding Bezier curve. Ultimately, the final result from the conversion can be expressed in the forms of the Bezier control points. As a result, these Bezier curve represents the given handwritten curve image.
{"title":"Approximating Online Handwritten Image by Bézier Curve","authors":"Taweechai Nuntawisuttiwong, N. Dejdumrong","doi":"10.1109/CGIV.2012.24","DOIUrl":"https://doi.org/10.1109/CGIV.2012.24","url":null,"abstract":"In this paper, a Bezier curve is construct to represent a hand-drawn image, expressed in the forms of a set of consecutive dots. Using input's sampling points, an online handwritten curve is converted into a vectored curve by Newton-Lagrange interpolation. Although Newton-Lagrange curve can be used well in the approximation of the handwritten curve, their polynomials are not appropriate in the applications of computer aided geometric design (CAGD). Therefore, Newton-Lagrange curve will then be converted into a corresponding Bezier curve. Ultimately, the final result from the conversion can be expressed in the forms of the Bezier control points. As a result, these Bezier curve represents the given handwritten curve image.","PeriodicalId":365897,"journal":{"name":"2012 Ninth International Conference on Computer Graphics, Imaging and Visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122938298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A picture is worth a thousand words. To take advantage of powerful human vision, we generate visualizations for people to view and to understand the underlying data. However, these a thousand words do not necessarily tell the truth about the data. A good visualization can make the data understanding process effective, while a bad visualization may hinder the process, even convey misleading information. To produce effective visualizations, it is important for us to have a good understanding of how people actually perceive and process the visual information. People view visualizations using their eyes, and tracking their eye movements can be a useful method for this purpose. In this talk, I will present a series eye tracking studies on how people read graphs. These studies demonstrate that: 1) eye tracking is an effective method for gaining insights into how people read graphs, and 2) how obtained insights from eye tracking can be used to inform the design of visualizations.
{"title":"Window to the Soul: Tracking Eyes to Inform the Design of Visualizations","authors":"Weidong Huang","doi":"10.1109/CGIV.2012.11","DOIUrl":"https://doi.org/10.1109/CGIV.2012.11","url":null,"abstract":"A picture is worth a thousand words. To take advantage of powerful human vision, we generate visualizations for people to view and to understand the underlying data. However, these a thousand words do not necessarily tell the truth about the data. A good visualization can make the data understanding process effective, while a bad visualization may hinder the process, even convey misleading information. To produce effective visualizations, it is important for us to have a good understanding of how people actually perceive and process the visual information. People view visualizations using their eyes, and tracking their eye movements can be a useful method for this purpose. In this talk, I will present a series eye tracking studies on how people read graphs. These studies demonstrate that: 1) eye tracking is an effective method for gaining insights into how people read graphs, and 2) how obtained insights from eye tracking can be used to inform the design of visualizations.","PeriodicalId":365897,"journal":{"name":"2012 Ninth International Conference on Computer Graphics, Imaging and Visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122162875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a newly constructed rational quadratic trigonometric Bézier curve with two shape parameters is presented. The purposed curve enjoys all the geometric properties of the traditional rational quadratic Bézier curve. The local control on the shape of the curve can be attained by altering the values of the shape parameters as well as the weight. The curve exactly represents some quadratic trigonometric curves such as the arc of an ellipse and the arc of a circle and best approximates the ordinary rational quadratic Bézier curve.
{"title":"The Rational Quadratic Trigonometric Bézier Curve with Two Shape Parameters","authors":"U. Bashir, M. Abbas, A. A. Majid, J. Ali","doi":"10.1109/CGIV.2012.22","DOIUrl":"https://doi.org/10.1109/CGIV.2012.22","url":null,"abstract":"In this paper, a newly constructed rational quadratic trigonometric Bézier curve with two shape parameters is presented. The purposed curve enjoys all the geometric properties of the traditional rational quadratic Bézier curve. The local control on the shape of the curve can be attained by altering the values of the shape parameters as well as the weight. The curve exactly represents some quadratic trigonometric curves such as the arc of an ellipse and the arc of a circle and best approximates the ordinary rational quadratic Bézier curve.","PeriodicalId":365897,"journal":{"name":"2012 Ninth International Conference on Computer Graphics, Imaging and Visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128587704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a Thai font type recognition on Thai document by using Scale-invariant feature transform (SIFT). The features are extracted by Scale-invariant feature transform (SIFT) that is widely used in image processing. Sift is an algorithm for detecting local features in order to find similar objects. Our system contains ten fonts and ten text images in each font. We use ten text images each font total one hundred images for our experiment. Our results show accuracy for 97.37% for ten Thai fonts.
{"title":"Thai Font Type Recognition Using SIFT","authors":"Pitchaya Jamjuntr, N. Dejdumrong","doi":"10.1109/CGIV.2012.23","DOIUrl":"https://doi.org/10.1109/CGIV.2012.23","url":null,"abstract":"This paper presents a Thai font type recognition on Thai document by using Scale-invariant feature transform (SIFT). The features are extracted by Scale-invariant feature transform (SIFT) that is widely used in image processing. Sift is an algorithm for detecting local features in order to find similar objects. Our system contains ten fonts and ten text images in each font. We use ten text images each font total one hundred images for our experiment. Our results show accuracy for 97.37% for ten Thai fonts.","PeriodicalId":365897,"journal":{"name":"2012 Ninth International Conference on Computer Graphics, Imaging and Visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133949142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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