“…Cap defect detection results: Existing image segmentation methods are mainly divided into the following categories: threshold-based, edge-based [ 24 , 25 ] and methods based on specific theories. Since the captured image usually contains spot-like Gaussian noises and may have uneven surfaces and inhomogeneous illuminations, the contrast between the defects and the background information is usually not that high.…”
In the beverage, food and drug industry, more and more machine vision systems are being used for the defect detection of Polyethylene Terephthalate (PET) bottle caps. In this paper, in order to address the result of cylindrical distortions that influence the subsequent defect detection in the imaging process, a very fast image stitching algorithm is proposed to generate a panorama planar image of the surface of PET bottle caps. Firstly, the three-dimensional model of the bottle cap is established. Secondly, the relative poses among the four cameras and the bottle cap in the three-dimensional space are calculated to obtain the mapping relationship between three-dimensional points on the side surface of the bottle cap and image pixels taken by the camera. Finally, the side images of the bottle cap are unfolded and stitched to generate a planar image. The experimental results demonstrate that the proposed algorithm unfolds the side images of the bottle cap correctly and very fast. The average unfolding and stitching time for 1.6-megapixel color caps image can reach almost 123.6 ms.
“…Cap defect detection results: Existing image segmentation methods are mainly divided into the following categories: threshold-based, edge-based [ 24 , 25 ] and methods based on specific theories. Since the captured image usually contains spot-like Gaussian noises and may have uneven surfaces and inhomogeneous illuminations, the contrast between the defects and the background information is usually not that high.…”
In the beverage, food and drug industry, more and more machine vision systems are being used for the defect detection of Polyethylene Terephthalate (PET) bottle caps. In this paper, in order to address the result of cylindrical distortions that influence the subsequent defect detection in the imaging process, a very fast image stitching algorithm is proposed to generate a panorama planar image of the surface of PET bottle caps. Firstly, the three-dimensional model of the bottle cap is established. Secondly, the relative poses among the four cameras and the bottle cap in the three-dimensional space are calculated to obtain the mapping relationship between three-dimensional points on the side surface of the bottle cap and image pixels taken by the camera. Finally, the side images of the bottle cap are unfolded and stitched to generate a planar image. The experimental results demonstrate that the proposed algorithm unfolds the side images of the bottle cap correctly and very fast. The average unfolding and stitching time for 1.6-megapixel color caps image can reach almost 123.6 ms.
“…The proposed “edge detector” ICWFL is applied to generate the edge map gradients E ( x , y ) from smooth gray scale eye images I ( x , y ) which works well for accurate detection of edges and to test the accuracy of the proposed ICWFL edge detector for iris segmentation, we have done a comparative analysis of some existing edge detectors with the proposed method. The concept behind the ICWFL approach is referred in Kumawat and Panda ( 2021 ). The following algorithm steps elaborates the working of ICWFL edge detector: Step 1 : “Canny edge detection (CED)” method used “Gaussian filter” for image smoothing.…”
Section: Proposed Methodology For Segmenting An Irismentioning
confidence: 99%
“… Fig. 6 Edge map gradients of various edge detectors noisy iris images a gray scale of sampled noisy image; b horizontal edge mapped iris; c vertical edge mapped iris; d roberts (Bhardwaj and Mittal, 2012 ) vertical edge mapped iris; e sobel (El-Khamy et al, 2000 ) vertical edge mapped iris; f Prewitt (Gonzalez and Woods, 2002 ) vertical edge mapped iris; g Canny ( 1986 ) vertical edge mapped iris; h ICA (Xuan and Hong, 2017 ) vertical edge mapped iris; i BE3 (Mittal et al, 2019 ) vertical edge mapped iris; j ICWFL (Kumawat and Panda, 2021 ) vertical edge mapped iris …”
Section: Proposed Methodology For Segmenting An Irismentioning
confidence: 99%
“…The results are shown in Tables 2 . It is found that ICWFL (Kumawat and Panda, 2021 ) outperforms the above six edge detection techniques. In order to get a “smooth” and “noise-free” image from the noisy edge map image from the above step, we have applied proposed hybrid restoration fusion filter (HRFF).…”
Section: Introductionmentioning
confidence: 99%
“…A comparative analysis of six standard edge detection techniques with own proposed ICWFL method is carried out. That is Roberts (Bhardwaj and Mittal, 2012 ), Sobel (El-Khamy et al, 2000 ), Prewitt (Gonzalez and Woods, 2002 ), Canny ( 1986 ), ICA (Xuan and Hong, 2017 ), BE3 (Mittal et al, 2019 ) and ICWFL (Kumawat and Panda, 2021 ). The results are shown in Tables 2 .…”
In an automated iris recognition system, in order to get higher accuracy, we should have an efficient iris segmentation process. The reliability of accurate “iris recognition” system largely depends on the accuracy of segmentation process. Traditional “iris segmentation” methods are unable to detect the exact boundaries of iris and pupil, which is time consuming and also highly sensitive to noise. To overcome these problems, we have proposed an improved Wildes method (IWM) for segmentation in iris recognition system. The proposed algorithm consists of two major steps before applying Wildes method for segmentation: edge detection of iris and pupil from a noisy eye image with improved Canny with fuzzy logic (ICWFL) and removal of unwanted noise from above step with a hybrid restoration fusion filter (HRFF). A comparative study of various edge detection techniques is performed to prove the efficiency of ICWFL method. Similarly, the proposed method is tested with various noise densities from 10 to 95 dB. Also the working of the proposed HRFF is compared with some existing smoothing filters. Various experiments have been performed with the help of iris database of IIT_Delhi. Both visual and numerical results prove the efficiency of the proposed algorithm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
