Fuzzy Index to Evaluate Edge Detection in Digital Images

• DOI: 10.1371/journal.pone.0131161
• Publication Date: 2015-06-26T22:52:08Z
• Authors: Felicitas Perez-O...; Olivia Mendoza; Patricia Melin; Juan R. Castro; Antonio Rodriguez...; Oscar Castillo
• Keywords: Science; Q; R; Signal Processing, Computer-Assisted; 02 engineering and technology; Signal-To-Noise Ratio; Image Enhancement; Fuzzy Logic; Image Processing, Computer-Assisted; 0202 electrical engineering, electronic engineering, information engineering; Medicine; Humans; Algorithms; Research Article

In literature, we can find different metrics to evaluate the detected edges in digital images, like Pratt's figure of merit (FOM), Jaccard's index (JI) and Dice's coefficient (DC). These compare two first one is reference image, second image. It important mention that all existing must binarize images before their evaluation. Binarization step causes information be lost because an incomplete image being evaluated. this paper, propose a fuzzy (FI) for edge evaluation does not use binarization step. order process edges, are represented form calculations made with sets operators Euclidean distance between both images. Our proposed compared most used using synthetic good results.