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大小: 10.82M文件类型: .rar金币: 1下载: 0 次发布日期: 2021-04-18
- 语言: Matlab
- 标签: matlab SIFT RANSAC forgery detection RANSAC+sift+ color sift+ransac
资源简介
the folder gives information about the image forgery detection. detection is made by examining the sift and ransac features of the image. color processing is done as a preprocessing step.
代码片段和文件信息
function [Lhits] = ADABOOST_te(adaboost_modelte_func_handletest_set...
true_labels)
%
% ADABOOST TESTING
%
% [Lhits] = ADABOOST_te(adaboost_modelte_func_handletrain_set
% true_labels)
%
% ‘te_func_handle‘ is a handle to the testing function of a
% learning (weak) algorithm whose prototype is shown below.
%
% [Lhitserror_rate] = test_func(modeltest_setsample_weightstrue_labels)
% model: the output of train_func
% test_set: a KxD dimensional matrix each of whose row is a
% testing sample in a D dimensional feature space.
% sample_weights: a Dx1 dimensional vector the i-th entry
% of which denotes the weight of the i-th sample.
% true_labels: a Dx1 dimensional vector the i-th entry of which
% is the label of the i-th sample.
% L: a Dx1-array with the predicted labels of the samples.
% hits: number of hits calculated with the comparison of L and
% true_labels.
% error_rate: number of misses divided by the number of samples.
%
% It is the corresponding testing
% module of the function that is specified in the training phase.
% ‘test_set‘ is a NxD matrix where N is the number of samples
% in the test set and D is the dimension of the feature space.
% ‘true_labels‘ is a Nx1 matrix specifying the class label of
% each corresponding sample‘s features (each row) in ‘test_set‘.
% ‘adaboost_model‘ is the model that is generated by the function
% ‘ADABOOST_tr‘.
%
% ‘L‘ is the likelihoods that are assigned by the ‘ADABOOST_te‘.
% ‘hits‘ is the number of correctly predicted labels.
%
% Specific Properties That Must Be Satisfied by The Function pointed
% by ‘func_handle‘
% ------------------------------------------------------------------
%
% Notice: Labels must be positive integer values from 1 upto the number classes.
%
% Bug Reporting: Please contact the author for bug reporting and comments.
%
% Cuneyt Mertayak
% email: cuneyt.mertayak@gmail.com
% version: 1.0
% date: 21/05/2007
%
hypothesis_n = length(adaboost_model.weights);
sample_n = size(test_set1);
class_n = length(unique(true_labels));
temp_L = zeros(sample_nclass_nhypothesis_n); % likelihoods for each weak classifier
% for each weak classifier likelihoods of test samples are collected
for i=1:hypothesis_n
[temp_L(::i)hitserror_rate] = te_func_handle(adaboost_model.parameters{i}...
test_setones(sample_n1)true_labels);
temp_L(::i) = temp_L(::i)*adaboost_model.weights(i);
end
L = sum(temp_L3);
hits = sum(likelihood2class(L)==true_labels);
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 741072 2000-01-01 01:00 image forgery with siftand ransac\image forgery\1.jpg
文件 703685 2002-01-23 15:18 image forgery with siftand ransac\image forgery\3.jpg
文件 2916 2008-09-03 13:17 image forgery with siftand ransac\image forgery\ADABOOST_te.m
文件 4452 2008-09-03 13:17 image forgery with siftand ransac\image forgery\ADABOOST_tr.m
文件 415 2013-12-01 21:44 image forgery with siftand ransac\image forgery\adaptivethreshold.m
文件 461 2011-01-25 15:15 image forgery with siftand ransac\image forgery\appendimages.m
文件 2314 2009-09-08 23:37 image forgery with siftand ransac\image forgery\colImgSeg.m
文件 800 2013-12-01 21:45 image forgery with siftand ransac\image forgery\CreateDataba
文件 1848 2011-11-01 08:18 image forgery with siftand ransac\image forgery\demo.m
文件 30673 2011-10-20 06:42 image forgery with siftand ransac\image forgery\erode.jpg
文件 4696 2013-01-25 14:32 image forgery with siftand ransac\image forgery\example.asv
文件 4698 2013-01-25 14:28 image forgery with siftand ransac\image forgery\example.m
文件 2057049 2013-11-01 11:51 image forgery with siftand ransac\image forgery\Exposing Digital Image Forgeries by Illumination.pdf
文件 188440 2001-09-17 16:22 image forgery with siftand ransac\image forgery\face.jpg
文件 794 2011-11-01 07:42 image forgery with siftand ransac\image forgery\face_detection.asv
文件 7411 2013-08-11 11:11 image forgery with siftand ransac\image forgery\face_detection.m
文件 460 2014-02-27 10:16 image forgery with siftand ransac\image forgery\findHomography.m
文件 103647 2011-01-16 22:50 image forgery with siftand ransac\image forgery\hall1.JPG
文件 102984 2011-01-16 22:50 image forgery with siftand ransac\image forgery\hall2.JPG
文件 1934 2014-02-27 10:16 image forgery with siftand ransac\image forgery\imMosaic.m
文件 14227 2009-09-08 23:37 image forgery with siftand ransac\image forgery\Input.JPG
文件 342 2013-12-01 21:37 image forgery with siftand ransac\image forgery\knn.m
文件 1334 2011-03-24 11:57 image forgery with siftand ransac\image forgery\license.txt
文件 241 2014-02-27 10:16 image forgery with siftand ransac\image forgery\likelihood2class.m
文件 3537 2013-10-15 09:19 image forgery with siftand ransac\image forgery\main.m
文件 7050 2013-12-02 22:09 image forgery with siftand ransac\image forgery\mainproject.m
文件 260 2014-02-08 12:33 image forgery with siftand ransac\image forgery\mosaicTest.asv
文件 318 2014-02-08 12:34 image forgery with siftand ransac\image forgery\mosaicTest.m
文件 14530 2014-02-27 11:07 image forgery with siftand ransac\image forgery\mosaic_a.jpg
文件 50481 2011-01-25 15:06 image forgery with siftand ransac\image forgery\mosaic_hall.jpg
............此处省略47个文件信息
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