Bangladesh Wood Image Dataset for Wood Type and Processing Stage Recognition.

Description

The dataset consists of 1940 high-resolution RGB images of commonly used wood species in Bangladesh, collected to support image-based wood identification using machine learning and computer vision techniques. The images represent four wood species: Shegun , Mehgoni , Gamari and Barbati.Each wood species is captured across three processing stages: Raw Wood, Cut Wood, and Before Burnish, reflecting practical conditions observed in timber markets and furniture workshops. Images were collected from multiple locations in Dhaka, Bangladesh, including timber markets, wood mills, and furniture factories, between November 2025 and January 2026.Image acquisition was performed using various mobile phone cameras under diverse natural lighting conditions, angles, and distances to ensure visual variability. All images were converted to JPG format and resized to a uniform resolution of 4032 × 3024 pixels to maintain consistency for supervised learning applications.The dataset is organized in a structured folder hierarchy based on wood species, with subfolders for each processing stage. This organization enables straightforward use for classification, recognition, and industrial quality assessment tasks in artificial intelligence–based research. Categories for this data Computer Science Artificial Intelligence Machine Learning Computer Vision Image Processing Agricultural Informatics Forestry and Wood Science

Institutions

• Southeast University

  Dhaka Division, Dhaka

Categories

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