Hi am developing an application which is use wavelet transformation for feature extraction.
I am not able to translate 2d Discrete wavelets Transformation for with haar transformation . I need a source code to do it. Is there any java library already available to do this . Please give me detail about this.
try this one, it's in java.Check if your wavelet is there https://code.google.com/p/jwave/
Related
I am Working on Face Recognition using OpenCV c++: I have tested the code OpenCV provides for PCA: It returns me Eigen Vectors and Mean, But how can i use that to test an image for Recognition?
I read Articles to understand the process of PCA..I can implement the covariance Matrix,weights and all manually but I wanted to try OpenCV PCA function.
Please Do help
Take a look the links below I think it should be useful:
Opencv's FaceRecognizer class:
http://docs.opencv.org/trunk/modules/contrib/doc/facerec/index.html
Eigenfaces in OpenCV
http://docs.opencv.org/trunk/modules/contrib/doc/facerec/facerec_tutorial.html#eigenfaces-in-opencv
I have a 3D matrix (very large, let call it L) and a 3D small one (very small, let call it S) and want to use OpenCV to find the closest pattern in L.
Does OpenCV do it for me? If yes, how I should use it?
Thanks.
What you need is the Point Cloud Library, which is an open source library to work with 3D data. I can tell you from my experience, that learning to use this library is very similar to learning OpenCV because many developers work for Willow Garage, the main sponsor of OpenCV.
If you go to the PCL tutorials you will find three useful sections to solve your problem:
1) finding features in your 3D point cloud, that you can later use for matching
2) 3D object recognition based on correspondence grouping
3) Point cloud registration using methods like iterative closest point, and feature matching
No, OpenCV doesn't have anything for this.
Do you have sparse pointcloud or just 3-dim matrix?
For 3-dim matrix you can use phase correlation using FFT. Good library is FFTW
OpenCV has added some neat tools to accomplish this kind of task
Surface Matching https://docs.opencv.org/master/d9/d25/group__surface__matching.html
Silhouette based 3D tracking https://docs.opencv.org/master/d4/dc4/group__rapid.html
Convolutional Neural Network https://docs.opencv.org/master/d9/d02/group__cnn__3dobj.html
I need to train the sample image set to classification of them. But i have bit knowledge about the SVM technique to do the coding stuff. please help me to do the programming part of that.
The OpenCV documentation of the SVM provides a small example on how to use it: link
Where can I find :
"Direct Linear Transform" algorithm (and the method to compute homography matrix) coded in Java/C++/C#/C ?
From Wikipedia:
OpenCV is a complete (open and free) computer vision software library that has many routines related to homography estimation (findHomography)
I was going the K-means algorithm as a technique for clustering images, as part of my project in the area of Image Processing. In the process, I decided to code using OpenCV libraries. So, can somebody help me in coding the algorithm in C++ using OpenCV. I can manage well, if some code snippet is provided. I just started learning about the OpenCV environment. Thank you for reading this. I ll be grateful for your help. waiting for a reply!
Before you implement clustering (k-means or otherwise), you need to figure out how to compare one image vs the other. This is usually dependent on the type of images you have, what features you can extract (colors, edges, shapes etc.).
A simple way of comparing 2 images would be to use the SURF features and compare to other images' SURF features. The OpenCV samples should get you started on how to extract SURF.
Other approaches would be to extract edges, shapes, color histograms and compare to others. Once you have done so, clustering should be fairly straightforward.
Check mlem.cpp and cxmatrix.cpp.
If you're new to OpenCV, have a look at my website.. http://aishack.in/ I've put up some tutorials/articles on vision and vision algorithms. Hopefully they'll help!