FOSSEE-Internship · sidn77 · Jul 7, 2017 · Nov 8, 2017 · Nov 8, 2017 · Nov 8, 2017
diff --git a/data/argset3.dat b/data/argset3.dat
diff --git a/data/emclassi3.yml b/data/emclassi3.yml
diff --git a/data/knnclassi3.yml b/data/knnclassi3.yml
diff --git a/help/builder_help.sce b/help/builder_help.sce
@@ -0,0 +1,21 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Shamika Mohanan
+// Organization: FOSSEE, IIT Bombay
+// Email: [email protected]
+// This file must be used under the terms of the BSD.
+// This source file is licensed as described in the file LICENSE, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// https://opensource.org/licenses/BSD-3-Clause
+
+mode(-1)
+lines(0)
+
+toolbox_title = "FOSSEE_Image_Processing_Toolbox"
+
+help_dir = get_absolute_file_path('builder_help.sce');
+
+tbx_builder_help_lang("en_US", help_dir);
+
+clear toolbox_title;
diff --git a/help/builder_help.sce~ b/help/builder_help.sce~
@@ -0,0 +1,21 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Harpreet Singh
+// Organization: FOSSEE, IIT Bombay
+// Email: [email protected]
+// This file must be used under the terms of the BSD.
+// This source file is licensed as described in the file LICENSE, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// https://opensource.org/licenses/BSD-3-Clause
+
+mode(-1)
+lines(0)
+
+toolbox_title = "FOSSEE_Optimization_Toolbox"
+
+help_dir = get_absolute_file_path('builder_help.sce');
+
+tbx_builder_help_lang("en_US", help_dir);
+
+clear toolbox_title;
diff --git a/help/en_US/blobAnalysis.xml b/help/en_US/blobAnalysis.xml
@@ -0,0 +1,94 @@
+<?xml version="1.0" encoding="UTF-8"?>
+
+<!--
+ *
+ * This help file was generated from blobAnalysis.sci using help_from_sci().
+ *
+ -->
+
+<refentry version="5.0-subset Scilab" xml:id="blobAnalysis" xml:lang="en"
+          xmlns="http://docbook.org/ns/docbook"
+          xmlns:xlink="http://www.w3.org/1999/xlink"
+          xmlns:svg="http://www.w3.org/2000/svg"
+          xmlns:ns3="http://www.w3.org/1999/xhtml"
+          xmlns:mml="http://www.w3.org/1998/Math/MathML"
+          xmlns:scilab="http://www.scilab.org"
+          xmlns:db="http://docbook.org/ns/docbook">
+
+  <refnamediv>
+    <refname>blobAnalysis</refname>
+    <refpurpose>Detects blob in the source image</refpurpose>
+  </refnamediv>
+
+
+<refsynopsisdiv>
+   <title>Calling Sequence</title>
+   <synopsis>
+   [blob] = blobAnalysis(srcImg)
+   [blob] = blobAnalysis(srcImg, Name, Value)
+
+   </synopsis>
+</refsynopsisdiv>
+
+<refsection>
+   <title>Parameters</title>
+   <variablelist>
+   <varlistentry><term>srcImg:</term>
+      <listitem><para> The input image Matrix.</para></listitem></varlistentry>
+   <varlistentry><term>ROI:</term>
+      <listitem><para> This defines a particular in the image in of which you want the features.</para></listitem></varlistentry>
+   <varlistentry><term>filterByThreshold:</term>
+      <listitem><para> This filter compares the intensity of a binary image at the center of a</para></listitem></varlistentry>
+   <varlistentry><term>filterByArea:</term>
+      <listitem><para> Extracted blobs have an area between minArea (inclusive) and maxArea (exclusive).</para></listitem></varlistentry>
+   <varlistentry><term>filterByCircularity:</term>
+      <listitem><para> Extracted blobs have circularity ( 4∗π∗Areaperimeter∗perimeter) between</para></listitem></varlistentry>
+   <varlistentry><term>filterByConvexity:</term>
+      <listitem><para> Extracted blobs have convexity (area / area of blob convex hull) between minConvexity</para></listitem></varlistentry>
+   </variablelist>
+</refsection>
+
+<refsection>
+   <title>Description</title>
+   <para>
+The function uses SimpleBlobDetector function to detect the blobs then it checks for different Name
+Value pair arguments and accordingly returns the parameters of the blob such as 2D coordinates of the
+blob, size of the blob.
+   </para>
+   <para>
+The Name-Value pair may be any of following types<itemizedlist><listitem><para>bool filterByArea, vector [minArea maxArea]</para></listitem><listitem><para>bool filterByCircularity, vector [minCircularity maxCircularity]</para></listitem><listitem><para>bool filterByConvexity, vector [minConvexity maxConvexity]</para></listitem><listitem><para>double ROI, vector </para></listitem><listitem><para>bool filterByThreshold, vector [minThreshold maxThreshold]</para></listitem></itemizedlist>
+   </para>
+   <para>
+</para>
+</refsection>
+
+<refsection>
+   <title>Examples</title>
+   <programlisting role="example"><![CDATA[
+img_2 = imread("/images/blob.jpg", 0);
+
+lis1 = blobAnalysis(img_2, "filterByThreshold", [200, 255]);
+lis2 = blobAnalysis(img_2, "filterByCircularity", [0.1, 0.9]);
+lis3 = blobAnalysis(img_2, "filterByArea", [1500, 1600]);
+
+dimage1 = drawKeypoints(img_2, lis1.Points, "color", [0, 255, 0]);
+dimage2 = drawKeypoints(img_2, lis2.Points, "color", [0, 255, 0]);
+dimage3 = drawKeypoints(img_2, lis3.Points, "color", [0, 255, 0]);
+
+   ]]></programlisting>
+</refsection>
+
+<refsection>
+   <title>See also</title>
+   <simplelist type="inline">
+   <member><link linkend="imread,">drawKeypoints</link></member>
+   </simplelist>
+</refsection>
+
+<refsection>
+   <title>Authors</title>
+   <simplelist type="vert">
+   <member>Deepshikha</member>
+   </simplelist>
+</refsection>
+</refentry>
diff --git a/help/en_US/build_help.sce b/help/en_US/build_help.sce
@@ -0,0 +1,17 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Shamika Mohanan
+// Organization: FOSSEE, IIT Bombay
+// Email: [email protected]
+// This file must be used under the terms of the BSD.
+// This source file is licensed as described in the file LICENSE, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// https://opensource.org/licenses/BSD-3-Clause
+
+help_lang_dir = get_absolute_file_path('build_help.sce');
+
+tbx_build_help(TOOLBOX_TITLE, help_lang_dir);
+
+clear help_lang_dir;
+
diff --git a/help/en_US/build_help.sce~ b/help/en_US/build_help.sce~
@@ -0,0 +1,17 @@
+// Copyright (C) 2015 - IIT Bombay - FOSSEE
+//
+// Author: Shamika Mohanan
+// Organization: FOSSEE, IIT Bombay
+// Email: [email protected]
+// This file must be used under the terms of the BSD.
+// This source file is licensed as described in the file LICENSE, which
+// you should have received as part of this distribution.  The terms
+// are also available at
+// https://opensource.org/licenses/BSD-3-Clause
+
+help_lang_dir = get_absolute_file_path('build_help.sce');
+
+tbx_build_help(TOOLBOX_TITLE, help_lang_dir);
+
+clear help_lang_dir;
+
diff --git a/help/en_US/decorrstretch.xml b/help/en_US/decorrstretch.xml
@@ -0,0 +1,74 @@
+<?xml version="1.0" encoding="UTF-8"?>
+
+<!--
+ *
+ * This help file was generated from decorrstretch.sci using help_from_sci().
+ *
+ -->
+
+<refentry version="5.0-subset Scilab" xml:id="decorrstretch" xml:lang="en"
+          xmlns="http://docbook.org/ns/docbook"
+          xmlns:xlink="http://www.w3.org/1999/xlink"
+          xmlns:svg="http://www.w3.org/2000/svg"
+          xmlns:ns3="http://www.w3.org/1999/xhtml"
+          xmlns:mml="http://www.w3.org/1998/Math/MathML"
+          xmlns:scilab="http://www.scilab.org"
+          xmlns:db="http://docbook.org/ns/docbook">
+
+  <refnamediv>
+    <refname>decorrstretch</refname>
+    <refpurpose>Applies decorrelation stretch to an image.</refpurpose>
+  </refnamediv>
+
+
+<refsynopsisdiv>
+   <title>Calling Sequence</title>
+   <synopsis>
+   outputImage = decorrstretch(image);
+
+   </synopsis>
+</refsynopsisdiv>
+
+<refsection>
+   <title>Parameters</title>
+   <variablelist>
+   <varlistentry><term>image:</term>
+      <listitem><para> Input image.</para></listitem></varlistentry>
+   </variablelist>
+</refsection>
+
+<refsection>
+   <title>Description</title>
+   <para>
+This function applies decorrelation stretch to an input image which causes the image to enhance
+by way of amplifying image difference.
+   </para>
+   <para>
+</para>
+</refsection>
+
+<refsection>
+   <title>Examples</title>
+   <programlisting role="example"><![CDATA[
+i = imread("images/lena.jpg");
+outputImage = decorrstretch(i);
+imshow(i);
+
+   ]]></programlisting>
+</refsection>
+
+<refsection>
+   <title>See also</title>
+   <simplelist type="inline">
+   <member><link linkend="imread">imread</link></member>
+   <member><link linkend="imshow">imshow</link></member>
+   </simplelist>
+</refsection>
+
+<refsection>
+   <title>Authors</title>
+   <simplelist type="vert">
+   <member>Dhruti Shah</member>
+   </simplelist>
+</refsection>
+</refentry>
diff --git a/help/en_US/detectAndComputeORB.xml b/help/en_US/detectAndComputeORB.xml
@@ -0,0 +1,106 @@
+<?xml version="1.0" encoding="UTF-8"?>
+
+<!--
+ *
+ * This help file was generated from detectAndComputeORB.sci using help_from_sci().
+ *
+ -->
+
+<refentry version="5.0-subset Scilab" xml:id="detectAndComputeORB" xml:lang="en"
+          xmlns="http://docbook.org/ns/docbook"
+          xmlns:xlink="http://www.w3.org/1999/xlink"
+          xmlns:svg="http://www.w3.org/2000/svg"
+          xmlns:ns3="http://www.w3.org/1999/xhtml"
+          xmlns:mml="http://www.w3.org/1998/Math/MathML"
+          xmlns:scilab="http://www.scilab.org"
+          xmlns:db="http://docbook.org/ns/docbook">
+
+  <refnamediv>
+    <refname>detectAndComputeORB</refname>
+    <refpurpose>Oriented FAST and rotated BRIEF (ORB) is used to detect and compute the corners in an image.</refpurpose>
+  </refnamediv>
+
+
+<refsynopsisdiv>
+   <title>Calling Sequence</title>
+   <synopsis>
+   [orb] = detectAndComputeORB(srcImg)
+   [orb] = detectAndComputeORB(srcImg, Name(same as the ones given under description), Value, ...)
+
+   </synopsis>
+</refsynopsisdiv>
+
+<refsection>
+   <title>Parameters</title>
+   <variablelist>
+   <varlistentry><term>srcImg:</term>
+      <listitem><para> The input image Matrix</para></listitem></varlistentry>
+   <varlistentry><term>ROI:</term>
+      <listitem><para> This defines a particular in the image in of which you want the features.</para></listitem></varlistentry>
+   <varlistentry><term>maxFeatures:</term>
+      <listitem><para> The maximum number of features to retain.</para></listitem></varlistentry>
+   <varlistentry><term>scaleFactor:</term>
+      <listitem><para> Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical pyramid,</para></listitem></varlistentry>
+   <varlistentry><term>nLevels:</term>
+      <listitem><para> The number of pyramid levels. The smallest level will have linear size equal to</para></listitem></varlistentry>
+   <varlistentry><term>edgeThreshold:</term>
+      <listitem><para> This is size of the border where the features are not detected. It should roughly match</para></listitem></varlistentry>
+   <varlistentry><term>firstLevel:</term>
+      <listitem><para> It should be 0 in the current implementation.</para></listitem></varlistentry>
+   <varlistentry><term>scoreType:</term>
+      <listitem><para> The default HARRIS_SCORE (flag value = 0) means that Harris algorithm is used to rank features</para></listitem></varlistentry>
+   <varlistentry><term>patchSize:</term>
+      <listitem><para> Size of the patch used by the oriented BRIEF descriptor. Of course, on smaller pyramid layers</para></listitem></varlistentry>
+   <varlistentry><term>fastThreshold:</term>
+      <listitem><para> The threshold value used for feature detection.</para></listitem></varlistentry>
+   </variablelist>
+</refsection>
+
+<refsection>
+   <title>Description</title>
+   <para>
+Oriented FAST and rotated BRIEF (ORB) is a fast robust local feature detector, first presented
+by Ethan Rublee in  2011,that can be used in computer vision tasks like object recognition
+or 3D reconstruction.
+It is based on the FAST keypoint detector and the visual descriptor BRIEF (Binary Robust
+Independent Elementary Features).
+Its aim is to provide a fast and efficient alternative to SIFT.
+   </para>
+   <para>
+The Name-Value pair may be any of following types<itemizedlist><listitem><para> edgeThreshold  </para></listitem><listitem><para> fastThreshold  </para></listitem><listitem><para> firstLevel     </para></listitem><listitem><para> maxFeatures    </para></listitem><listitem><para> nLevels        </para></listitem><listitem><para> patchSize      </para></listitem><listitem><para> scaleFactor    </para></listitem><listitem><para> scoreType      </para></listitem></itemizedlist>
+   </para>
+   <para>
+</para>
+</refsection>
+
+<refsection>
+   <title>Examples</title>
+   <programlisting role="example"><![CDATA[
+img_1 = imread("images/checkerBoard.jpg", 0);
+img_2 = imread("images/chess.jpg", 0);
+lis1 = detectAndComputeORB(img_1);
+lis2 = detectAndComputeORB(img_2);
+dimage = drawKeypoints(img_2, lis2.Points);
+[matches, distance] = matchFeatures(lis1.Features, lis1.Features, "Method", "Exhaustive", "Metric", "Hamming");
+matchedImage = drawMatch(img_1, img_2, lis1.Points, lis2.Points, matches, distance);
+
+   ]]></programlisting>
+</refsection>
+
+<refsection>
+   <title>See also</title>
+   <simplelist type="inline">
+   <member><link linkend="imread">imread</link></member>
+   <member><link linkend="drawMatch">drawMatch</link></member>
+   <member><link linkend="drawKeypoints">drawKeypoints</link></member>
+   <member><link linkend="matchFeatures">matchFeatures</link></member>
+   </simplelist>
+</refsection>
+
+<refsection>
+   <title>Authors</title>
+   <simplelist type="vert">
+   <member>Siddhant Narang</member>
+   </simplelist>
+</refsection>
+</refentry>