Presented is a fast image search algorithm that can significantly reduce similarity calculation compared to a full comparison of every database image. For fast searches a tree is constructed by successfully dividing nodes into the desired depth level ...
Presented is a fast image search algorithm that can significantly reduce similarity calculation compared to a full comparison of every database image. For fast searches a tree is constructed by successfully dividing nodes into the desired depth level by working from the root to the leaf nodes using the k-means algorithm. When the query is completed, we traverse the tree top-down by minimizing the route taken between the query image and node controid until we meet the undivided nodes. Within undivided nodes, the algorithm of triangle inequality is used to find the images most similar to the query.