Image Segmentation for Mobile Phone Film Defects Under Low Contrast

Chunjian Hua; Jinhua Guo; Ying Chen

doi:10.3788/LOP57.201013

Laser & Optoelectronics Progress, Volume. 57, Issue 20, 201013(2020)

Image Segmentation for Mobile Phone Film Defects Under Low Contrast

Chunjian Hua^1,2、*, Jinhua Guo^1,2, and Ying Chen³

Author Affiliations

¹School of Mechanical Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China

²Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment & Technology, Wuxi, Jiangsu 214122, China;

³School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China

show less

Abstract Get PDF(in Chinese)

Figures & Tables(13)

Fig. 1. Relation between the base number R(x, y) and the index γ in Gamma function

Download full size

Fig. 2. Comparison of two stretching methods

Download full size

Fig. 3. Comparison of the enhancement effect for scratch 1. (a) SSR; (b) algorithm in Ref.[4]; (c) CLAHE; (d) our algorithm

Download full size

Fig. 4. Comparison of the enhancement effect for scratch 2. (a) SSR; (b) algorithm in Ref.[4]; (c) CLAHE; (d) our algorithm

Download full size

Fig. 5. Comparison of the enhancement effect for scratch 3. (a) SSR; (b) algorithm in Ref.[4]; (c) CLAHE; (d) our algorithm

Download full size

Fig. 6. Comparison of the enhancement effect for crease 1. (a) SSR; (b) algorithm in Ref.[4]; (c) CLAHE; (d) our algorithm

Download full size

Fig. 7. Comparison of the enhancement effect for crease 2. (a) SSR; (b) algorithm in Ref.[4]; (c) CLAHE; (d) our algorithm

Download full size

Fig. 8. Marked results graphs. (a) Defect enhancement image; (b) gradient image; (c) marked image

Download full size

Fig. 9. Segmentation results of OTSU. (a) Fig. 3; (b) Fig. 4; (c) Fig. 5; (d) Fig. 6; (e) Fig. 7

Download full size

Fig. 10. Segmentation results of our algorithm. (a) Fig. 3; (b) Fig. 4; (c) Fig. 5; (d) Fig. 6; (e) Fig. 7

Download full size

Table 1. Comparison results of contrast of different algorithms

View table

Table 1. Comparison results of contrast of different algorithms

Algorithm	Fig.3	Fig.4	Fig.5	Fig.6	Fig.7
SSR	0.012	0.022	0.029	0.070	0.052
Algorithm in Ref.[4]	0.135	0.066	0.103	0.114	0.011
CLAHE	0.008	0.016	0.022	0.057	0.044
Our algorithm	0.019	0.040	0.040	0.083	0.084
Original image	0.007	0.014	0.019	0.043	0.027

Table 2. Comparison results of information entropy of different algorithms

View table

Table 2. Comparison results of information entropy of different algorithms

Algorithm	Fig.3	Fig.4	Fig.5	Fig.6	Fig.7
SSR	0.036	0.177	0.154	1.075	0.433
Algorithm in Ref.[4]	1.344	0.178	0.097	1.058	0.398
CLAHE	0.040	0.178	0.250	1.036	0.471
Our algorithm	0.042	0.195	0.197	1.291	0.541
Original image	0.034	0.154	0.154	0.865	0.358

Table 3. Comparison of time-consuming of different algorithms unit: s
View table
Table 3. Comparison of time-consuming of different algorithms unit: s
Algorithm Fig.3 Fig.4 Fig.5 Fig.6 Fig.7
SSR 0.319 0.301 0.309 0.308 0.493
Algorithm in Ref.[4] 6.325 8.138 9.074 10.236 10.334
CLAHE 0.313 0.293 0.250 0.259 0.303
Our algorithm 0.396 0.378 0.378 0.440 0.487

Tools

Get Citation

Copy Citation Text

Chunjian Hua, Jinhua Guo, Ying Chen. Image Segmentation for Mobile Phone Film Defects Under Low Contrast[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201013

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites