Robust feature identification for image-based object recognition

A system for identifying robust features within a training image, the system comprising:

• a processor;
• a memory device;
• and
• a feature detector executable on the processor according to software instructions stored in the memory device, the feature detector being configured to:
• generate training features by applying a feature detection algorithm to the training image, each training feature having a training feature location within the training image;
• transform at least a portion of the training image into a transformed image in accordance with a predefined image transformation;
• generate transform features by applying the feature detection algorithm to the transformed image, each transform feature having a transform feature location within the transformed image;
• map the training feature locations of the training features to corresponding training feature transformed locations within the transformed image in accordance with the predefined image transformation;
• and
• compile a robust feature set by selecting robust features, wherein each robust feature represents a training feature having a training feature transformed location proximal to a transform feature location of one of the transform features.

A computer program product embedded in a non-transitory computer readable medium comprising instructions executable by a computer processor to identify robust features within an image, the instructions being executable by a computer processor to execute processing comprising:

• generating training features by applying a feature detection algorithm to the training image, each training feature having a training feature location within the training image;
• transforming at least a portion of the training image into a transformed image in accordance with a predefined image transformation;
• generating transform features by applying the feature detection algorithm to the transformed image, each transform feature having a transform feature location within the transformed image;
• mapping the training feature locations of the training features to corresponding training feature transformed locations within the transformed image in accordance with the predefined image transformation;
• and
• compiling a robust feature set by selecting robust features, wherein each robust feature represents a training feature having a training feature transformed location proximal to a transform feature location of one of the transform features.