鱼的分类和识别

【实例简介】
编写matlab程序进行鱼的分类和识别，对相应数据集进行训练达到很高的准确率
【实例截图】
【核心代码】
fishRecognition
└── fishRecognition
├── features.mat
├── fish_recog
│   ├── a_history.m
│   ├── append_acceptImage.m
│   ├── append_addSpeciesSubfeature.m
│   ├── append_ami_afinv.txt
│   ├── append_ami_cafmi.m
│   ├── append_ami_cm.m
│   ├── append_ami_readinv.m
│   ├── append_CalculateSim_byResult.m
│   ├── append_cleanBinaryImage.m
│   ├── append_compareChisquare.m
│   ├── append_complexmoment.m
│   ├── append_construct_hier.m
│   ├── append_constructRecursiveNode.m
│   ├── append_constructRecursiveNode_parfor.m
│   ├── append_convertlabel.m
│   ├── append_convertScore_allNodes_15.m
│   ├── append_convertscore.m
│   ├── append_createTreeFromTable.m
│   ├── append_createZeroMeanUnitVarianceImage.m
│   ├── append_fastcoprops.m
│   ├── append_filteClassGroup.m
│   ├── append_filteClass.m
│   ├── append_findSimilarPair_coSim.m
│   ├── append_findSimilarPair_GraphDistance.m
│   ├── append_findSimilarPair_self.m
│   ├── append_findSimilarPair_top2.m
│   ├── append_fishShapeContext.m
│   ├── append_gaborfilter.m
│   ├── append_getDistanceForFish_Eu.m
│   ├── append_getDistanceForFish_Mh.m
│   ├── append_getFeatureDistances.m
│   ├── append_getFeatureDistances_rory.m
│   ├── append_getMedianKNN.m
│   ├── append_getSpecificImage.m
│   ├── append_hcolor.m
│   ├── append_hier_assignFSSubset.m
│   ├── append_hierFeatureSelection.m
│   ├── append_hierScoreToFlat.m
│   ├── append_imscomatrix.m
│   ├── append_interp_contour.m
│   ├── append_mergeSplitResult.m
│   ├── append_normalizecolor.m
│   ├── append_normalizefeature.m
│   ├── append_orienCurve.m
│   ├── append_orienFish.m
│   ├── append_resizeFish.m
│   ├── append_rotateFish_d.m
│   ├── append_sc_bdry_extract_3.m
│   ├── append_sc_bookstein.m
│   ├── append_sc_dist2.m
│   ├── append_sc_gaussker.m
│   ├── append_sc_get_samples_1.m
│   ├── append_sc_hist_cost_2.m
│   ├── append_sc_hungarian.m
│   ├── append_sc_sc_compute.m
│   ├── append_seperateFish.m
│   ├── append_shrinkImage.m
│   ├── append_sortDistances.m
│   ├── append_sumResult.m
│   ├── append_testNodeSplit.m
│   ├── append_testTrinityNode.m
│   ├── append_timeString.m
│   ├── CheckData.m
│   ├── classify_crossValidation.m
│   ├── classify_featureselection_fbtrain.m
│   ├── classify_featureselection_fw.m
│   ├── classify_featureselection_fw_parfor.m
│   ├── classify_featureselection_pool.m
│   ├── classify_featureselection_unsimilar.m
│   ├── classify_GMM_crossValidation.m
│   ├── classify_GMM_fs_fw.m
│   ├── classify_GMM.m
│   ├── classify_GMM_predict.m
│   ├── classify_GMM_train.m
│   ├── classify_HierSVM_allNode_predict.m
│   ├── classify_HierSVM_evaluate.m
│   ├── classify_HierSVM.m
│   ├── classify_HierSVM_Node_predict.m
│   ├── classify_HierSVM_predict.m
│   ├── classify_HierSVM_train.m
│   ├── classify_HierSVM_TreePredict.m
│   ├── classify_KNN.m
│   ├── classify_rejectionGMM.m
│   ├── classify_SVM_evaluate.m
│   ├── classify_SVM.m
│   ├── classify_SVM_predict.m
│   ├── classify_SVM_train.m
│   ├── classify_testHsplit.m
│   ├── computeGLCM.m
│   ├── confusionmat.m
│   ├── crossvalind.m
│   ├── data_23Species.mat
│   ├── de2bi.m
│   ├── feature_AffineMomentInvariant.m
│   ├── feature_anna_binMatrix.m
│   ├── feature_anna_phogDescriptor.m
│   ├── feature_anna_phog.m
│   ├── feature_bog.m
│   ├── feature_CSScorner.m
│   ├── feature_curvecorner.m
│   ├── feature_densityfeature.m
│   ├── feature_dsift.m
│   ├── feature_gaborfeature.m
│   ├── feature_generateFeatureVector.m
│   ├── feature_getColourHistogram.m
│   ├── feature_getComplexMoments.m
│   ├── feature_getCoOccurrenceMatrix.m
│   ├── feature_getFourierDescriptors.m
│   ├── feature_getNormalizedRG.m
│   ├── feature_histogram_features_from_image.m
│   ├── feature_histogram_features.m
│   ├── feature_kerneltrans.m
│   ├── feature_MaskAreaRatio.m
│   ├── feature_trainPHOWdict.m
│   ├── getFileNamefromID.m
│   ├── getSegmentedTailColourHistogram.m
│   ├── getVideoIDfromName.m
│   ├── gmm_mixtures4.m
│   ├── gmm_multinorm.m
│   ├── GrabCut.m
│   ├── GraphCutConstr.mexglx
│   ├── GraphCut.m
│   ├── GraphCutMex.mexglx
│   ├── grp2idx.m
│   ├── improveFishContour.m
│   ├── integra_svm_normal.m
│   ├── interface_classification.m
│   ├── interface_constructBinaryHier.m
│   ├── interface_generateFeatureSet.m
│   ├── interface_normalizeFeatureFromPrefix.m
│   ├── interface_normalizeFeatureSet.m
│   ├── interface_prediction.m
│   ├── interface_recognizeFishFromImage.m
│   ├── interface_rejection23.m
│   ├── interface_rejection.m
│   ├── interface_trainBGOTFromImage.m
│   ├── libsvm.dll
│   ├── libsvmpredict.mexa64
│   ├── libsvmpredict.mexglx
│   ├── libsvmpredict.mexw32
│   ├── libsvmpredict.mexw64
│   ├── libsvmread.mexa64
│   ├── libsvmread.mexw32
│   ├── libsvmread.mexw64
│   ├── libsvmtrain.mexa64
│   ├── libsvmtrain.mexglx
│   ├── libsvmtrain.mexw32
│   ├── libsvmtrain.mexw64
│   ├── libsvmwrite.mexa64
│   ├── libsvmwrite.mexw32
│   ├── libsvmwrite.mexw64
│   ├── loadFishData.m
│   ├── LocalColorModel.m
│   ├── parseArgs.m
│   ├── polygon_string.m
│   ├── preprocess_rotate.m
│   ├── queryFishDetectionMYSQL.m
│   ├── readFrames.m
│   ├── RecognizeFish.m
│   ├── result_1vs1.m
│   ├── result_areaundercurve.m
│   ├── result_convertClassCell.m
│   ├── result_cv_evaluate.m
│   ├── result_drawsingle_feature.m
│   ├── result_evaluate.m
│   ├── result_trajvote_byScore.m
│   ├── result_trajvote.m
│   ├── result_trajvote_single.m
│   ├── script_featureSelection_1vsRest_GMM.m
│   ├── script_featureSelection_1vsRest.m
│   ├── script_featureSelection_hierTree.m
│   ├── script_HPC_NodeSplit.m
│   ├── script_NodeSplit_N1_obselete.m
│   ├── script_NodeSplit_N1_reGroup.m
│   ├── script_NodeSplit_N2_reGroup.m
│   ├── segmentFishDetection.m
│   └── SmoothnessTerm.m
├── image.mat
├── interface_trainBGOTFromImage_update.m
├── README
├── sample_predictSpecies.m
├── sample_trainBGOT.m
└── sample_trainGMM.m

2 directories, 184 files