Data for : Corner Detection Algorithms Evaluation

The Corner Detection Algorithms Evaluation Dataset (CDAED) is a well-designed dataset to evaluate corner detection algorithms. The dataset contains original data like MNIST digits, geometric structure images, and chessboard patterns, and the processed results obtained from our new Geo-Heinz Mean Corner Detection Algorithm. By showing both raw data and algorithmic output, CDAED enables researchers to quantitatively and qualitatively compare corner detection performance in controlled environments, facilitating reproducibility and improving feature detection research.