Merge pull request #3635 from vpisarev/updated_readme

updated readme for several opencv_contrib modules (done by Gary)
Sorry for not putting it through pull requests, but I was citing it in GSoC idea projects and wanted the Google Reviewers to see something visually more compelling.

modules/alphamat/README.md

@@ -1,9 +1,14 @@
 # Computer Vision based Alpha Matting
 
+![Trimap Alphamat Example from Askoy et al 2017](https://github.com/opencv/opencv_contrib/assets/810997/5cafae51-18e1-4e75-9035-6b40c9a064cb)
+
+
+
 This project was part of the Google Summer of Code 2019.
 
-####Student: Muskaan Kularia
-####Mentor: Sunita Nayak
+#### Student: Muskaan Kularia
+#### Mentor: Sunita Nayak
+
 ***
 Alphamatting is the problem of extracting the foreground from an image. Given the input of an image and its corresponding trimap, we try to extract the foreground from the background.
 
@@ -20,4 +25,4 @@ This project is implementation of "[Designing Effective Inter-Pixel Information
 
 [4] Qifeng Chen, Dingzeyu Li, Chi-Keung Tang, "[KNN Matting](http://dingzeyu.li/files/knn-matting-tpami.pdf)", IEEE TPAMI, 2013.
 
-[5] Yagiz Aksoy, "[Affinity Based Matting Toolbox](https://github.com/yaksoy/AffinityBasedMattingToolbox)".
+[5] Yagiz Aksoy, "[Affinity Based Matting Toolbox](https://github.com/yaksoy/AffinityBasedMattingToolbox)".

modules/aruco/README.md

@@ -3,10 +3,15 @@ ArUco Marker Detection
 
 **ArUco**
 
+![markers](https://github.com/opencv/opencv_contrib/assets/810997/8d587456-f27f-49e4-9540-28a0477d43fc)
+
 ArUco markers are easy to detect pattern grids that yield up to 1024 different patterns. They were built for augmented reality and later used for camera calibration. Since the grid uniquely orients the square, the detection algorithm can determing the pose of the grid.
 
 **ChArUco**
 
+![screen_charuco](https://github.com/opencv/opencv_contrib/assets/810997/64610da1-ee06-406c-a19b-006b02ac44fd)
+
+
 ArUco markers were improved by interspersing them inside a checkerboard called ChArUco. Checkerboard corner intersections provide more stable corners because the edge location bias on one square is countered by the opposite edge orientation in the connecting square. By interspersing ArUco markers inside the checkerboard, each checkerboard corner gets a label which enables it to be used in complex calibration or pose scenarios where you cannot see all the corners of the checkerboard.
 
-The smallest ChArUco board is 5 checkers and 4 markers called a "Diamond Marker".
+The smallest ChArUco board is 5 checkers and 4 markers called a "Diamond Marker".

modules/line_descriptor/README.md

@@ -2,3 +2,11 @@ Binary Descriptors for Line Segments
 ====================================
 
 This module shows how to extract line segments from an image by 2 different methods: First segmenting lines with Line Segment Detector LSDDetector and then (or just) using the Binary Descriptor to get the lines and give them a descriptor -- BinaryDescriptor. Finally, we can then match line segments using the BinaryDescriptorMatcher class.
+
+## Two views of a builing
+![Two views of a building](https://github.com/opencv/opencv_contrib/assets/810997/e5d438f9-5745-447c-b189-111a16fcdc76)
+
+## Line segments detected and matched
+![LSD segments detected and matched](https://github.com/opencv/opencv_contrib/assets/810997/22d89e93-24ad-4939-b48c-9223c76889bd)
+
+* [Image examples from CSDN](https://blog.csdn.net/Small_Munich/article/details/87990946)