Gas Meter Digit Segmentation Step 1: ROI

When dealing with high-resolution meter images, performing ROI (Region of Interest) localization first is key to boosting accuracy and saving scan time.

I noticed an interesting feature on most gas meters: the decimal digits on the far right are typically red.

In the world of computer vision, this red color acts as a natural "anchor."

My Implementation Logic:

1. Downsample First: To simulate a resource-constrained MCU environment, I downsample the image first to save memory.

2. Hunt for the "Splash of Red": Using OpenCV’s inRange function, I isolate the red color space to pinpoint the decimal area.

3. 

   Geometry-Based ROI Estimation: It’s a game of coordinates. Once the red box is located, I calculate the integer section by shifting the window to the left (typically twice the width of the red zone).

4. 

   The "Toast Slicing" Step: This is the most satisfying part. I use Vertical Projection to "slice" the image like a loaf of bread, separating each individual digit.

   
   

Current Progress: The digit segmentation is complete.

The next step is to feed these "slices" into a Algorithm for character recognition.