How to get quality of Homography matrix?

Question

Problem statement :  Image stitching/mosaic to be done with set of images (taken from same camera with certain level of overlap) which are captured either vertically or horizontally (any one of them)

Definitions : Train Image : The Image to be transformed.

Query Image : The image to be stitched after transformation with train Image.

Approaches Taken : The following points describe the approach:

1. Image registration :  The key points based ORB (Orient fast and rotate brief) feature is used for registration of images.The opencv function such as cv2.ORB_create(nfeatures=10000,WTA_K=4) is used. The detect and describe will give features for train and query images.
2. Calibration : Calibrate the pixels to be stitched. i.e the above feature based detection is used to find the absolute position for the calibration to happen. This is where we search the key points of both images and find equivalent ones to find position for calibration to happen. Used Brute force method to match between train and query images. By taking features mathed, we get the Homography matrix by using cv2.findHomography function. Used the RANSAC (Random sample consensus) method , which is very sensitive to reprojThresh value. I used a pretty high value of 90, which worked for about 10 images stitching (covering the next step of blending). But then later images started working for a low value of 3 or so. Which made me dynamically find this reprojthresh. Which is difficult to set , as our evaluation of stitching is subjective, hence not getting quantification to say this Homography matrix is perfect for stitching. I have used inlier ratio and determinant of homography to check on the quality of transformation. But not able to generalize it for all images.
3. Image blending :  This is the final stage where the position found above is mapped on to perspective projection. This will map the calibrated positions into transformed images which can be blended with other images. Here I am using a very simple blending mechanism after the homography matrix transforms it. which just finds locations of the transformed image and pad it with another image (assumed to be properly aligned).This stage is assumed to be correct, as I keep the homography transformed image as a checking mechanism to confirm this.

Questions :

1. Does this approach look good ? if not, please suggest alternatives.
2. If so, how to check homography matrix quality in terms of quantification, so that it can be automatically used for further blending.
3. Homography matrix generation using RANSAC is used multiple times to fine tune the homography, but the transformed image is misaligned. is this advisable ?