Results 291 to 300 of about 483,454 (329)

Directional geometric histogram feature extraction and applications

Multimedia Tools and Applications, 2017
Image feature has been a hot research topic within the field of computer vision, with a wide scope of direct impacts on detection, recognition, image retrieval and pose estimation, etc. In this paper, we propose a novel image feature: Directional Geometric Histogram (DGH) which adopts directional geometric approximation from the geometric Bandelet ...
Hong Han, Jingxiang Gou
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Image tampering detection using noise histogram features

2015 IEEE International Conference on Digital Signal Processing (DSP), 2015
With the rapid development of digital image editing tools, the authenticity of digital images becomes questionable in recent years. Image tampering detection is a technology that detects tampered images by using intrinsic image regularities. However, existing intrinsic image regularities are designed for one specific type of tampering operations.
Jiayuan Fan, Tao Chen, Jiuwen Cao
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Identifying computer generated graphics VIA histogram features

2011 18th IEEE International Conference on Image Processing, 2011
Discriminating computer generated graphics from photographic images is a challenging problem of digital forensics. An important approach to this issue is to explore usual image statistics. In this way, when the statistical distributions (i.e., histograms) of some types of residual images are established, previous works usually apply operations on these
Ruoyu Wu, Xiaolong Li, Bin Yang
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Local histogram filtering utilizing feature-selective templates

SPIE Proceedings, 1992
Local histogram filtering utilizing feature selective templates consists of ordering the elements of the subimage histogram contained in the support of a nine element square template translating over the image, rather than ordering the subimage intensity values, as in standard order statistic filtering.
Tom J. McMurray, John A. Pearce
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Enhancing SURF Feature Matching Using Colour Histograms

2011 Irish Machine Vision and Image Processing Conference, 2011
A strategy is proposed that enhances the local feature matching capabilities of the SURF descriptor by utilising colour histograms. The results compare variations of the RGB, HSV and Opponent colour spaces on a dataset of image pairs that undergo illumination, viewpoint and translational changes.
Tony Marrero Barroso, Paul F. Whelan
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Texture segmentation based on local feature histograms

2011 18th IEEE International Conference on Image Processing, 2011
This paper presents a convex vector-valued active contour model for texture segmentation. This model uses histograms of the semi-local region descriptor and image intensity for measuring the similarity of image regions. We use the Quadratic-Chi histogram distance to compare the dissimilarity of histograms.
Liyan Ma, Jian Yu
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Evolutionary Spatial Histogram Features for Vehicle Detection

Journal of Information and Computational Science, 2014
The evolutionary methods for detection aims to improve the accuracy and efiective of detection task. In this paper, an evolutionary object detection approach is proposed. The proposed algorithm employs the 5-fold validation as fltness criterion to direct the selection of templates, which is vital for creating spatial histogram features. In evolutionary
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Non-rigid image registration using local histogram-based features

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
This paper proposes a new non-rigid image registration method based on the formulation of the Demons algorithm. The proposed method utilizes combined geometric moments of local histogram to form new feature images. It greatly improves the accuracy of the original Demons algorithm, which is easy to get trapped at local minima during optimization.
Yishan, Luo, Albert C S, Chung
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Histogram Features-Based Fisher Linear Discriminant for Face Detection

Neural Computing and Applications, 2006
The face pattern is described by pairs of template-based histogram and Fisher projection orientation under the paradigm of AdaBoost learning in this paper. We assume that a set of templates are available first. To avoid making strong assumptions about distributional structure while still retaining good properties for estimation, the classical ...
Haijing Wang, Peihua Li, Tianwen Zhang
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Image Feature Extraction Using Diameter-Limited Gradient Direction Histograms

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979
Features extracted by operators which examine diameter-limited gradient direction histograms are important because they describe images of industrial workpieces efficiently and have the potential for rapid computation via special purpose hardware.
J, Birk, R, Kelley, N, Chen, L, Wilson
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