Implementing Spectral-Domain Feature Mapping for Sketch-Based Image Retrieval
Keywords:
Sketch-based image retrieval, spectral map coding, true and false regression, Gabor filter, content distortionAbstract
Sketch-based image retrieval (SBIR) has grown significantly in popularity across various real-time applications that use automated image processing. Examples of applications that use SBIR include banking, internet searching, and secure coding. On the other hand, these applications have a higher need for performance in terms of speed and accuracy. Because of the high cost of testing and the limited resources, the representative traits have to be narrowed down to be more selected for descriptive purposes and lowered in the count. The existing methods have low computational speed, more complexity and less accuracy. This paper presents a novel spectral deviation method in a sketch-based picture retrieval method. Spectral Coding Selective Feature Mapping (SpecCode SFM) is the name of the suggested technique. It was created by comparing the spatial correspondence between sketch images and their raw image counterparts. The suggested approach for retrieval passes the image as a free-hand sketch processing. This method tolerates scale and orientation and provides a sizable retrieval efficiency. The developed approach's findings are compared to those of cutting-edge techniques, and it is discovered that SpecCode SFM achieves 99.87% accuracy, 0.87 detection rate, 0.89 MCC, and 0.12 sec of computing time.
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