mser | Linear time Maximally Stable Extremal Regions implementation | Computer Vision library

I am comparing the performance of feature detection algorithms like Harris, ORB, MSER (OpenCV Python). I have two images of the same object taken from different viewpoints. Since I am just a beginner to this area, I am having trouble understanding what "pre-image" means in this context. How do I get the "pre-image"?

Detecting regions covariant with a class of transformations has now reached some maturity in the computer vision literature. The requirement for these regions is that they should correspond to the same pre-image for different viewpoints, i.e., their shape is not fixed but automatically adapts, based on the underlying image intensities, so that they are the projection of the same 3D surface patch.

I can't extract the detected regions by MSER in this image:

What I want to do is to save the green bounded areas. My actual code is this:

I have a service which captures the location of a user and updates database using retrofit. I want to stop the service automatically at 8 pm everyday if its running and also update the database that the user has punched out at 8 pm.

I want the service to start the manually but want the service to stop automatically if it is not stopped manually.

Here is my service class

I have background services which captures location from the users device but when I stop it using the stopService method from anther activity it does not stop and due to this the app crashes as the app is not able to send the lat long to server.

Note - I have a retrofit post request which is made to the server when the location is not null and also when I click on the stop service button in main activity the notification disappears from the device but actually the service does not stop and the location is logged in the logcat. But it is not posted to the server due to this timeout error is received and app crashes.

Here is the service class:

I am trying to implement character extraction from images in Python using the MSER in opencv. This is my code till now:

I am trying to develop a OCR system. I am trying to use MSER in order to extract character from an image and then passing the characters into a CNN to recognize those characters. Here is my code for character extraction:

I am using MSER from opencv-python to detect text using the code from this stackoverflow question. Can anyone help me understand why the contour p is being reshaped to (-1, 1, 2) before computing the convex hull of the objects?

The code is as below:

I want to cluster non-zero locations in a NumPy 2D array for MSER detection. Then I want to find the number of points in each cluster and remove those clusters which do not have number of points between some x and y (10 and 300).

I have tried clustering them by searching with neighbouring points but the method fails for concave-shaped non-zero clusters.

I try to use MSER algorithm to text detection. I use this code: