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- W2913544931 abstract "Target recognition and real time scene analysis have become increasingly important as tools in the automation industry. The ability to correctly identify an object in background noise, would solve a number of recognition problems varying from military target identification to automatic photo-interpretation. An algorithm is presented in this study which explores noisy background target recognition.The basis for this recognition process is an edge enhancement algorithm which extracts edges from an input scene. The edge enhanced target scene is searched with an edged object template and the correlation output displayed. High correlation peaks might either be suspected targets or high energy noise correlated with the edged template. To distinguish between these two conditions, the correlation peaks are used as central points for normalization of the input scene. An area equal to the size of the target is normalized to the template energy around each correlation central point, the rest of the image being blanked and the new scene is re-correlated with the template. This method of re-correlation is more efficient with respect to computer processing time than normalized correlation, therefore it provides a much faster method for noisy scene target recognition.If a correct target was the cause for the original correlation peak, a concentrated and intense re-correlation peak occurs with noise correlation dropping significantly. If the suspected target was not the cause for a correlation peak, normalization to the template energy drops the total energy producing a weak and dispersed re-correlation peak. The use of this algorithm produces positive target identification in noisy environments and opens up new possibilities in scene analysis." @default.
- W2913544931 created "2019-02-21" @default.
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- W2913544931 date "1985-01-01" @default.
- W2913544931 modified "2023-09-24" @default.
- W2913544931 title "Two-dimensional target recognition using a modified afit edge enhancement algorithm (normalization)" @default.
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