An Analytical Approach for Soil Classification Using Image Processing

Abstract

This research introduces a novel analytical approach for soil classification using image processing techniques, leveraging computer vision and machine learning advancements to enhance efficiency and accuracy. By analyzing high-resolution imagery, meaningful features are extracted to identify distinct soil types based on visual characteristics, streamlining the classification process and providing valuable insights into soil composition and distribution. With applications in environmental monitoring, precision agriculture, and land management, this methodology offers a comprehensive and innovative solution validated by experimental results, demonstrating its potential as a valuable tool for researchers and practitioners.