圖象邊緣檢測(cè)是計(jì)算機(jī)圖象處理的最基本步驟之一。由于噪聲的干擾和圖象光照不均勻等因素的影響,目前的圖象邊緣檢則方法還不能有效地檢測(cè)出各種不同模式的邊緣。在分析了幾種常用邊緣檢測(cè)方法及其存在的檢測(cè)精度不高，抗噪聲性能較差等不足基礎(chǔ)上，給出了一種基于遺傳算法和梯度算子的圖象邊緣檢測(cè)算法，該算法明顯提高了檢測(cè)精度和抗噪聲能力。
關(guān)鍵詞：圖象分割；邊緣檢測(cè)；遺傳算法
Abstract: Edge detection is one of the fundamental steps on the image processing. Due to the affection of the noise and unbalanced light source, no method can detect the edges of all modals. Through analyzing several kinds of edge detection methods, it is low in
detection precision, and it is relatively bad to resist noise performance. So this article
propose an edge detection algorithm in image based on the genetic algorithm and gradient
operators. This algorithm obviously improves the detection precision and the ability to
resist noise. further more analyzing its suitable environment through the experiment.
Key words: Image segmentation; Edge detection; Genetic algorithm