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authorshamikam2017-01-16 02:56:17 +0530
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+/*#******************************************************************************
+ ** IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+ **
+ ** By downloading, copying, installing or using the software you agree to this license.
+ ** If you do not agree to this license, do not download, install,
+ ** copy or use the software.
+ **
+ **
+ ** bioinspired : interfaces allowing OpenCV users to integrate Human Vision System models.
+ ** TransientAreasSegmentationModule Use: extract areas that present spatio-temporal changes.
+ ** => It should be used at the output of the cv::bioinspired::Retina::getMagnoRAW() output that enhances spatio-temporal changes
+ **
+ ** Maintainers : Listic lab (code author current affiliation & applications)
+ **
+ ** Creation - enhancement process 2007-2015
+ ** Author: Alexandre Benoit (benoit.alexandre.vision@gmail.com), LISTIC lab, Annecy le vieux, France
+ **
+ ** Theses algorithm have been developped by Alexandre BENOIT since his thesis with Alice Caplier at Gipsa-Lab (www.gipsa-lab.inpg.fr) and the research he pursues at LISTIC Lab (www.listic.univ-savoie.fr).
+ ** Refer to the following research paper for more information:
+ ** Strat, S.T.; Benoit, A.; Lambert, P., "Retina enhanced bag of words descriptors for video classification," Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European , vol., no., pp.1307,1311, 1-5 Sept. 2014 (http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6952461&isnumber=6951911)
+ ** Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011
+ ** This work have been carried out thanks to Jeanny Herault who's research and great discussions are the basis of all this work, please take a look at his book:
+ ** Vision: Images, Signals and Neural Networks: Models of Neural Processing in Visual Perception (Progress in Neural Processing),By: Jeanny Herault, ISBN: 9814273686. WAPI (Tower ID): 113266891.
+ **
+ **
+ ** License Agreement
+ ** For Open Source Computer Vision Library
+ **
+ ** Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+ ** Copyright (C) 2008-2011, Willow Garage Inc., all rights reserved.
+ **
+ ** For Human Visual System tools (bioinspired)
+ ** Copyright (C) 2007-2015, LISTIC Lab, Annecy le Vieux and GIPSA Lab, Grenoble, France, all rights reserved.
+ **
+ ** Third party copyrights are property of their respective owners.
+ **
+ ** Redistribution and use in source and binary forms, with or without modification,
+ ** are permitted provided that the following conditions are met:
+ **
+ ** * Redistributions of source code must retain the above copyright notice,
+ ** this list of conditions and the following disclaimer.
+ **
+ ** * Redistributions in binary form must reproduce the above copyright notice,
+ ** this list of conditions and the following disclaimer in the documentation
+ ** and/or other materials provided with the distribution.
+ **
+ ** * The name of the copyright holders may not be used to endorse or promote products
+ ** derived from this software without specific prior written permission.
+ **
+ ** This software is provided by the copyright holders and contributors "as is" and
+ ** any express or implied warranties, including, but not limited to, the implied
+ ** warranties of merchantability and fitness for a particular purpose are disclaimed.
+ ** In no event shall the Intel Corporation or contributors be liable for any direct,
+ ** indirect, incidental, special, exemplary, or consequential damages
+ ** (including, but not limited to, procurement of substitute goods or services;
+ ** loss of use, data, or profits; or business interruption) however caused
+ ** and on any theory of liability, whether in contract, strict liability,
+ ** or tort (including negligence or otherwise) arising in any way out of
+ ** the use of this software, even if advised of the possibility of such damage.
+ *******************************************************************************/
+
+#ifndef SEGMENTATIONMODULE_HPP_
+#define SEGMENTATIONMODULE_HPP_
+
+/**
+@file
+@date 2007-2013
+@author Alexandre BENOIT, benoit.alexandre.vision@gmail.com
+*/
+
+#include "opencv2/core.hpp" // for all OpenCV core functionalities access, including cv::Exception support
+
+namespace cv
+{
+namespace bioinspired
+{
+//! @addtogroup bioinspired
+//! @{
+
+/** @brief parameter structure that stores the transient events detector setup parameters
+*/
+struct SegmentationParameters{ // CV_EXPORTS_W_MAP to export to python native dictionnaries
+ // default structure instance construction with default values
+ SegmentationParameters():
+ thresholdON(100),
+ thresholdOFF(100),
+ localEnergy_temporalConstant(0.5),
+ localEnergy_spatialConstant(5),
+ neighborhoodEnergy_temporalConstant(1),
+ neighborhoodEnergy_spatialConstant(15),
+ contextEnergy_temporalConstant(1),
+ contextEnergy_spatialConstant(75){};
+ // all properties list
+ float thresholdON;
+ float thresholdOFF;
+ //! the time constant of the first order low pass filter, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 0.5 frame
+ float localEnergy_temporalConstant;
+ //! the spatial constant of the first order low pass filter, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 5 pixel
+ float localEnergy_spatialConstant;
+ //! local neighborhood energy filtering parameters : the aim is to get information about the energy neighborhood to perform a center surround energy analysis
+ float neighborhoodEnergy_temporalConstant;
+ float neighborhoodEnergy_spatialConstant;
+ //! context neighborhood energy filtering parameters : the aim is to get information about the energy on a wide neighborhood area to filtered out local effects
+ float contextEnergy_temporalConstant;
+ float contextEnergy_spatialConstant;
+};
+
+/** @brief class which provides a transient/moving areas segmentation module
+
+perform a locally adapted segmentation by using the retina magno input data Based on Alexandre
+BENOIT thesis: "Le système visuel humain au secours de la vision par ordinateur"
+
+3 spatio temporal filters are used:
+- a first one which filters the noise and local variations of the input motion energy
+- a second (more powerfull low pass spatial filter) which gives the neighborhood motion energy the
+segmentation consists in the comparison of these both outputs, if the local motion energy is higher
+to the neighborhood otion energy, then the area is considered as moving and is segmented
+- a stronger third low pass filter helps decision by providing a smooth information about the
+"motion context" in a wider area
+ */
+
+class CV_EXPORTS_W TransientAreasSegmentationModule: public Algorithm
+{
+public:
+
+
+ /** @brief return the sze of the manage input and output images
+ */
+ CV_WRAP virtual Size getSize()=0;
+
+ /** @brief try to open an XML segmentation parameters file to adjust current segmentation instance setup
+
+ - if the xml file does not exist, then default setup is applied
+ - warning, Exceptions are thrown if read XML file is not valid
+ @param segmentationParameterFile : the parameters filename
+ @param applyDefaultSetupOnFailure : set to true if an error must be thrown on error
+ */
+ CV_WRAP virtual void setup(String segmentationParameterFile="", const bool applyDefaultSetupOnFailure=true)=0;
+
+ /** @brief try to open an XML segmentation parameters file to adjust current segmentation instance setup
+
+ - if the xml file does not exist, then default setup is applied
+ - warning, Exceptions are thrown if read XML file is not valid
+ @param fs : the open Filestorage which contains segmentation parameters
+ @param applyDefaultSetupOnFailure : set to true if an error must be thrown on error
+ */
+ virtual void setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure=true)=0;
+
+ /** @brief try to open an XML segmentation parameters file to adjust current segmentation instance setup
+
+ - if the xml file does not exist, then default setup is applied
+ - warning, Exceptions are thrown if read XML file is not valid
+ @param newParameters : a parameters structures updated with the new target configuration
+ */
+ virtual void setup(SegmentationParameters newParameters)=0;
+
+ /** @brief return the current parameters setup
+ */
+ virtual SegmentationParameters getParameters()=0;
+
+ /** @brief parameters setup display method
+ @return a string which contains formatted parameters information
+ */
+ CV_WRAP virtual const String printSetup()=0;
+
+ /** @brief write xml/yml formated parameters information
+ @param fs : the filename of the xml file that will be open and writen with formatted parameters information
+ */
+ CV_WRAP virtual void write( String fs ) const=0;
+
+ /** @brief write xml/yml formated parameters information
+ @param fs : a cv::Filestorage object ready to be filled
+ */
+ virtual void write( cv::FileStorage& fs ) const=0;
+
+ /** @brief main processing method, get result using methods getSegmentationPicture()
+ @param inputToSegment : the image to process, it must match the instance buffer size !
+ @param channelIndex : the channel to process in case of multichannel images
+ */
+ CV_WRAP virtual void run(InputArray inputToSegment, const int channelIndex=0)=0;
+
+ /** @brief access function
+ @return the last segmentation result: a boolean picture which is resampled between 0 and 255 for a display purpose
+ */
+ CV_WRAP virtual void getSegmentationPicture(OutputArray transientAreas)=0;
+
+ /** @brief cleans all the buffers of the instance
+ */
+ CV_WRAP virtual void clearAllBuffers()=0;
+};
+
+/** @brief allocator
+@param inputSize : size of the images input to segment (output will be the same size)
+@relates bioinspired::TransientAreasSegmentationModule
+ */
+CV_EXPORTS_W Ptr<TransientAreasSegmentationModule> createTransientAreasSegmentationModule(Size inputSize);
+
+//! @}
+
+}} // namespaces end : cv and bioinspired
+
+
+#endif
+
+