# Weak-Edge Extraction of Nuclear Plate Fuel Neutron Images at Low Lining Degree
## 4 Results and Discussion  
In this section, subjective and objective assessments are used to verify the feasibility and effectiveness of the proposed algorithm. To make the evaluation more convincing, we compared our method with the Sobel operator and the traditional Canny algorithm, mainly due to the following considerations: 1. Most of the current state-of-the-art models on edge detection are developed based on visual transformers, which require large-scale datasets for training to obtain good experimental results, but the neutron images data in this paper are small and without official ground truth; 2. The latest edge detection models are suitable for specialized image types, such as visible images and infrared images, and we have not yet found particularly representative models; 3. Canny and Sobel are highly representative and versatile in the image edge detection field and still appear in the rest of the latest papers, just like the benchmark. Edge detection experiments were conducted on the neutron images obtained by the reactor-based neutron imaging system at the Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics, introduced in Section 2. These images contain different subjects (e.g., plate nuclear fuel elements, rod fuel elements, zirconium alloys, and mechanical structural components.) with a spatial resolution of 50 \(\upmu\)m, and a pixel resolution of 2048 \(\times\) 2048, and all images are in TIFF format. Our testing platform is implemented in 64-bit Windows 10 OS, with an Intel Core i5 2.45-GHz CPU and 4-GB of RAM. * Subjective evaluation  
In subjective evaluation, the results of the three edge-detection algorithms are compared side by side based on the intuitive visual effect. The experimental results are shown in Figure 5. The rows from top to bottom represent the original images, the edge images extracted by the Sobel operator, the Canny operator, and our proposed method, separately. From Figure 5, in terms of the detection effect of weak edges, it is observed that the Sobel operator cannot successfully detect the weak edges of aluminum cladding with low grayscale contrast. Although Canny gained more edge information than Sobel, there are many clear breaks and discontinuities in the extracted outer edges of the aluminum cladding because of its inflexible gradient thresholds. Furthermore, both algorithms detected many textures inside the fuel elements. In contrast, our proposed method has better results. It can suppress the texture information and obtain cleaner, complete, and continuous edges, both weak and strong. * Objective evaluation In an objective evaluation, we measured the continuity and accuracy of the edge quantitatively using two metrics, which were based on the connection component and figure of merit values. Reference [33] proposed an edge evaluation statistical criterion based on the connection component. It calculated the total number of detected edge-pixel points (A), the four-connection component number (B), the eight-connection component number (C), and ratios  
Figure 5: Edge extraction results of plate fuel neutron images: (**a**) Preprocessed images; (**b**) Sobel; (**c**) Canny; (**d**) proposed method. (C/A and C/B). The smaller C/A and C/B are the better the edge integrity and continuity. The statistical results of the three algorithms are shown in Table 2.  
The statistical results show that our proposed method has the lowest C/A and C/B of the three approaches, which indicates that it has higher edge integrity and a better unilateral edge response than the traditional ones. Compared with the Canny operator, the edge integrity of this method is improved by 64.1%. [PERSON] provides an edge evaluation quantitative metric based on figures of merit (FOM) values. We used it to further conclude whether or not the proposed method achieves the same edge-detection accuracy as the traditional ones. The _FOM_ is given by Equation (14).