Response Rank based Sketch-Content Image Retrieval Search System

Sketch-based searching is a method that allows users to draw generic search queries and return similar drawn images, giving more user control over their search content. Sketch-based image retrieval often needs to optimize the trade-off between efficiency and precision. Index structures are typically applied to large-scale databases to realize efficient retrievals. However, the performance can be affected by quantization errors. Sketch-based image retrieval systems that preserve the index structure are challenging. In this work, an effective sketch-based image retrieval approach with re ranking and relevance feedback schemes is implemented. The current approach makes full use of the semantics in query sketches and the top ranked images of the initial results. It also apply relevance feedback to find more relevant images for the input query sketch. The integration of the two schemes results in mutual benefits and improves the performance of sketch-based image retrieval.