added documentation

Makefile

@@ -13,15 +13,13 @@ PACKAGE_FILE_PATH=$(shell pwd)/lipase-$(LIPASE_VERSION).zip
 .PHONY: all
 all: test doc
 
-.PHONY:
+.PHONY: doc
-doc: doc/lipase.pdf
+doc:
+	cd doc; make 
 
-doc/lipase.pdf: doc/lipase.tex
+.PHONY: clean_doc
-	cd doc; latexmk 
-
-.PHONY:
 clean_doc:
-	cd doc; rm lipase.pdf lipase.aux lipase.fls lipase.log lipase.fdb_latexmk lipase.dvi; 
+	cd doc; make clean
 
 
 $(BUILD_ROOT_PATH)/jars/Lib/fr.univ-rennes1.ipr.lipase.lib.jar: $(LIB_SRC_FILES)
@@ -32,7 +30,7 @@ $(BUILD_ROOT_PATH)/jars/Lib/fr.univ-rennes1.ipr.lipase.lib.jar: $(LIB_SRC_FILES)
 		popd
 
 .PHONY: install_ij_opencv
-install_ij_opencv: 
+install_ij_opencv:
    # enable IJ-OpenCV-plugins site because it's disabled by default
 
     # graffy@graffy-ws2:~$ zcat /home/graffy/soft/Fiji.app/db.xml.gz | grep IJ-Op | grep -v "jar" | grep -v "<plu"

doc/Makefile

@@ -0,0 +1,29 @@
+RAW_IMAGES_ROOT?=/home/graffy/work/lipase/raw-images
+lipase.pdf: lipase.tex graphics
+	pdflatex lipase.tex
+
+# command used to convert traps sequences in the visible into png with maximum contrast
+TRAPS_VISIBLE_CONVERTER=convert -contrast-stretch 2%x1% -resize 25%
+
+GENERATED_GRAPHICS=\
+	graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000000_DM300_nofilter_vis_000.png \
+	graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000019_DM300_nofilter_vis_000.png \
+	graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000039_DM300_nofilter_vis_000.png
+
+.PHONY: graphics
+graphics: $(GENERATED_GRAPHICS)
+
+graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000000_DM300_nofilter_vis_000.png : $(RAW_IMAGES_ROOT)/res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000000_DM300_nofilter_vis_000.tif
+	$(TRAPS_VISIBLE_CONVERTER) "$<" "$@"
+
+graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000019_DM300_nofilter_vis_000.png : $(RAW_IMAGES_ROOT)/res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000019_DM300_nofilter_vis_000.tif
+	$(TRAPS_VISIBLE_CONVERTER) "$<" "$@"
+
+
+graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000039_DM300_nofilter_vis_000.png : $(RAW_IMAGES_ROOT)/res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000039_DM300_nofilter_vis_000.tif
+	$(TRAPS_VISIBLE_CONVERTER) "$<" "$@"
+
+.PHONY: clean
+clean:
+	rm -f $(GENERATED_GRAPHICS)
+	rm -f lipase.pdf lipase.aux lipase.fls lipase.log lipase.fdb_latexmk lipase.dvi; 

doc/graphics/readme.md

@@ -0,0 +1 @@
+the purpose of this file is to make sure the empty graphics directory can be part of the git repository (workaround to the fact that git doesn't version empty directories)

doc/lipase.tex

@@ -1,14 +1,26 @@
-\documentclass[a4paper]{article}
+\documentclass[a4paper, 10pt]{article}
 \usepackage[utf8]{inputenc}
+\usepackage{graphicx}
+\usepackage{subcaption}
+\usepackage[htt]{hyphenat} % allow hyphen inside texttt to avoid overfull hbox warnings
+\usepackage[english, french]{babel}
+\usepackage[margin=0.5in]{geometry} % default margins are too big for my taste: too much wasted space http://kb.mit.edu/confluence/pages/viewpage.action?pageId=3907057
+\usepackage{amsmath} % provides underset
+
+\hyphenation{tu-yau}
+
+
 \title{lipase}
 \author{Guillaume Raffy \and Véronique Vié }
 \begin{document}
+    \selectlanguage{english}
 
     \maketitle
 
     \section{catalog images}
 
         image prefix :
+        \selectlanguage{french}
         \begin{description}
             \item[AF]
             \item[blé] coupes de blé
@@ -45,5 +57,46 @@
             \item[cin2] autre échantillon similaire à cin1
             \item[cond5678] condition non réalistes
         \end{description}
+        \selectlanguage{english}
+
+    \section{computing background image for trap sequences}
+
+        Trap sequences show traps at fixed positions with particles that move over time, as shown in figure \ref{fig:trap_sequence1}. In order to detect the particles, we can subtract from each image a background image, which is an image of the scene without any particle.
+
+        If we suppose that particles are moving fast enough, we can estimate this background image $B$, as :
+
+        \begin{equation}
+            B(x,y) = \underset{t\in {1 \ldots T_{max}}}{\mathrm{median}} \{I(x,y,t)\} 
+        \end{equation}
+        where $I(x,y,t)$ is the value of the input sequence at time $t$ and on pixel position $(x,y)$ and $T_{max}$ is the number of frames in the sequence.
+
+        \begin{figure}
+            \centering
+            \begin{subfigure}[b]{0.3\textwidth}
+                \includegraphics[width=1.0\textwidth]{graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000000_DM300_nofilter_vis_000.png}
+                %\includegraphics[width=\textwidth]{1.png}
+                \caption{Frame 0}
+                %\label{fig:1}
+            \end{subfigure}
+            ~
+            \begin{subfigure}[b]{0.3\textwidth}
+                \includegraphics[width=1.0\textwidth]{graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000019_DM300_nofilter_vis_000.png}
+                %\includegraphics[width=\textwidth]{1.png}
+                \caption{Frame 19}
+                %\label{fig:1}
+            \end{subfigure}
+            ~
+            \begin{subfigure}[b]{0.3\textwidth}
+                \includegraphics[width=1.0\textwidth]{graphics/res_soleil2018_GGH_GGH_2018_cin2_phiG_I_327_vis_-40_1_Pos0_img_000000039_DM300_nofilter_vis_000.png}
+                %\includegraphics[width=\textwidth]{1.png}
+                \caption{Frame 39}
+                %\label{fig:1}
+            \end{subfigure}
+
+
+            \caption{Example of trap sequence (\texttt{res\_soleil2018/GGH/GGH\_2018\_cin2\_phiG\_I\_327\_vis\_-40\_1/Pos0})}
+            \label{fig:trap_sequence1}
+        \end{figure}
+        
 
 \end{document}

doc/notes/journal.md

@@ -0,0 +1,19 @@
+## 12/03/2020
+
+- graffy : investigations on how to compute white for sequences containing traps:
+    - `telemos.WhiteEstimator` is not suitable for a sequence containing traps, as the resulting white image displays. `telemos.WhiteEstimator` is expecting the input images to only contain small particles.
+    - supposing that particles move in the sequences containing trap, the white image can be computed by 
+
+
+## 17/03/2020
+
+- graffy
+    - I made some manual tests for extracting background of `res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0`. For this sequence, the median image provides a worse background image than the last frame of the sequence, which contains nearly no particle. So for now we'll use the last frame as a background for the moment, but we have to find a better background estimator than just the median image (an idea is for example to keep for each pixel the value that is the most frequent in the sequence)
+    - Some manual tests on the sequence `res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0` showed that subtracting the background image makes particles more obviusly visible, as expected. Applying a threshold allows to isolate the particles, but estimating the surface ofd particles from that will be tricky, as only the border of particles have a value which is very different from the background. Of course a fill hole operator could fill rthe particles but this can be fragile as the borders of particles are not always clearly visible on all its surrounding.
+    - a more promising solution for detecting particles would be to compute for each pixel :
+    	- the radial profile around the pixel
+    	- the radial variance profile around the pixel
+    	then, particle are the pixels for which
+    		- the radial variance is low (this means that there's a radial symmetry around the pixel)
+    		- and the radial profile shows a peak. The position of the peak gives the radius of the particle
+    	- In order to efficiently compute these radial profile and radial variance profiles on a whole image, convolutions methods can provide dramatic speedups. This technique has already been used in https://subversion.ipr.univ-rennes1.fr/repos/main/projects/antipode (`texori.py`). Unfortunately, I can't reuse this code as it makes extensive used of `numpy` (and imagej's jython doesn't support `numpy`)