everyone! I have a question about labeling images. Except for CVAT, which labeling tool is superior for keypoint detection annotation in images? Please inform me. Your suggestion is highly appreciated. Thanks.
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I am working on an image classification problem and the dataset comes in the following format :
class_1_folder : consists of images_folder and mask_folder
class_2_folder : consists of images_folder and mask_folder
I am quite new to the field and would like your advice on the use of the mask folders in general in classification tasks.
I did some research but I cannot find an understandable answer.
My thought is that I could use them to improve my classifier's metric results by helping to focus on specific parts of the image. Is this valid ? If yes, should I consider the convolution of the image with its mask before feeding the image to a classifier ?
Any help is much appreciated. Thank you.
I'm developing a image editor by webgl. I did some research with the existing apps which contains image dehaze effect, FotoJet and Polarr. Here are the example images exported by FotoJet and Polarr.
Original:
FotoJet:
Polarr:
So, what's the dehaze algorithm they used? I think their algorithm is different, can anyone help me figure out the algorithms?
I find the algorithm of Kaiming He at http://kaiminghe.com/cvpr09/. I think it's the solution.
The FotoJet and Polarr don't implement the perfect result as Kaiming He's Demo. I'll try it by myself.
I have an image (in very low quality):
I was wondering if there is any suggestions help me improve quality so I can read numbers plate on that image (not 100% but much as possible) by OpenCV?
Thanks in advance!
Since I am not able to comment I can suggest an answer here.
First if all, you should use a noise removal filter as median filter, followed by a laplacian filter or Canny or any edge detection filter to enhance the edges a little bit. You should choose convenient parameters for both filters. Remember, it is subjective from one person to another, so the parameters depends mainly on you.
I am want to make a simple application that will detect a patterns on the wall like the image below.
So the patterns will be pasted on the wall. The camera will rotate around 360 degrees and identify the pattern.
I asked someone I know in the EEE field, and he said that i could use OpenCV. But he said OpenCV can only recognize 1 pattern only. Is this true.
I am new to image processing. I hope someone can advice me on how i should approach this project. If there are any valuable reference, please share. Your help would be much appreciated.
Yes it true but not quite. You need only one pattern on image to use methods like Surf. But you can use contour analysis to recognize pattern like your image. Also you can use AdaBoost to find your patterns if they are more complexity.
OpenCv is only library and have some methods to image processing. You can use what suits you best.
There are many tutorials about AdaBoost, Surf/Sift/Orb/Brisk... Contour analysis is more complex.
Good Luck!
I am currently doing my thesis and it is about paper currency recognition.
My problem is I can't remove the vandals in the scanned images of the money. Does anyone know how to do this?
Thanks!
Apply the following image pre-processing techniques:
Image Resizing,
Binarization,
Marginal Noise Removal,
Skew Detection,
Adaptive Thresholding,
Image Smothening/Filter,
Erosion,
Dilation,
Search on this topics... This one is pretty tough. Goodluck.. :D