Abstract:
Most hand-crafted key-point detectors like Harris corner, MSER, SIFT, and SURF use pre-designed structures to detect corners, blobs, and junctions in images. These detectors are inflexible due to pre-designed structures.
Non-uniform illumination also greatly affects these detectors. To our knowledge, no efficient method exists to solve both problems at once.
This paper introduces a Sparse Coding-based Key-point detector (SCK) that is fully invariant to affine intensity change and independent of structure.
The proposed detector finds a key point in an image using a block complexity measure. A strength measure is also suggested for comparing and selecting detected key-points when the maximum number is limited.
This project theoretically verifies the detector’s desirable traits. The detector performs well in repeatability and matching score on three public datasets.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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