论文标题
边缘，角和边界检测中的传统方法
Traditional methods in Edge, Corner and Boundary detection
论文作者
论文摘要
这是一篇关于边缘，角和边界检测方法的传统方法的评论论文。边缘，角和边界检测方法有许多现实世界的应用。例如，在医学图像分析中，边缘检测器用于从给定图像中提取特征。在自动驾驶汽车等现代创新中，边缘检测和细分是最关键的事情。如果我们想检测运动或跟踪视频，则角探测器会有所帮助。我试图在任何可能的情况下比较探测器的结果，并讨论了图像预科以最大程度地减少噪声的重要性。现实世界图像用于验证探测器的性能和局限性。
This is a review paper of traditional approaches for edge, corner, and boundary detection methods. There are many real-world applications of edge, corner, and boundary detection methods. For instance, in medical image analysis, edge detectors are used to extract the features from the given image. In modern innovations like autonomous vehicles, edge detection and segmentation are the most crucial things. If we want to detect motion or track video, corner detectors help. I tried to compare the results of detectors stage-wise wherever it is possible and also discussed the importance of image prepossessing to minimise the noise. Real-world images are used to validate detector performance and limitations.
