‘m working on a project where I need to analyze images of house interiors and detect and tag different elements such as floors, walls, and countertops. I’m looking for guidance on how to approach this task using image processing or computer vision techniques.

Specifically, I want to develop a method to automatically identify and label these elements within an image. For example, I want to be able to differentiate between the floor, walls, and countertops accurately.

Could someone suggest algorithms or approaches that would be suitable for this task? Any libraries or frameworks that could simplify the implementation would also be appreciated.

Thank you!

What I’ve tried:
So far, I’ve experimented with basic edge detection algorithms and color segmentation methods, but I haven’t achieved satisfactory results. The edges of different elements often blend together, and the segmentation isn’t accurate enough to distinguish between floors, walls, and countertops reliably.

What I’m expecting:
I’m hoping to find more advanced techniques or algorithms that can handle the complexities of indoor scenes better. Ideally, I’m looking for methods that can leverage features like texture, shape, and possibly even contextual information to improve the accuracy of detection and tagging.

Any suggestions or insights on how to improve my approach would be greatly appreciated!