Threshold Segmentation and Length Measurement Algorithms for Irregular Curves in Complex Backgrounds

Ruan, Xusheng; Deng, Haixiao; Xu, Qiguo; Liu, Yang; He, Jun

doi:10.3390/s22155761

Cited by 2 publications

(1 citation statement)

References 24 publications

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“…The local thresholding based on FGPA proposed to solve the uneven illumination and reflection problem by adopting the mean value of neighbourhood blocks and Gaussian weighted sum design idea in the local neighbourhood [7]. An algorithm for more precise and faster segmentation of the target curve, known as quasi-bimodal threshold segmentation (QBTS), which converts the multimodal histogram into a quasi-bimodal histogram proposed by Ruan et al [8].…”

Section: A Threshold Based Segmentationmentioning

confidence: 99%

A Survey of Diverse Segmentation Methods in Image Processing

Goyal

Punam

2022

2022 IEEE International Conference on Current Development in Engineering and Technology (CCET)

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The importance of image-processing techniques has increased across a wide range of applications as a result of advancements in computer technology. An important stage in the processing of images is segmenting of images. The process of breaking a picture into groups that each have their own distinct characteristics and similar characteristics, such as intensity, texture, class, culture and colour is known as segmentation. Image segmentation has been done with many different algorithms and methods. In this article, study reviews various image segmentation technologies. This paper covered many segmentation methods, including Threshold, Edge Detection, Region-based, Neural Network Image Segmentation and Clustering in any economy to increase the quality of life. This study is helpful in deciding how to best apply image segmentation techniques, as well as in enhancing their precision and effectiveness, in order to achieve the main goal of developing new algorithms.

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Section: A Threshold Based Segmentationmentioning

confidence: 99%

A Survey of Diverse Segmentation Methods in Image Processing

Goyal

Punam

2022

2022 IEEE International Conference on Current Development in Engineering and Technology (CCET)

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Photometric stereo multi-information fusion unsupervised anomaly detection algorithm

Lan,

Shi

2024

Appl. Opt.

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Due to different materials, product surfaces are susceptible to light, shadow, reflection, and other factors. Coupled with the appearance of defects of various shapes and types, as well as dust, impurities, and other interfering influences, normal and abnormal samples are difficult to distinguish and a common problem in the field of defect detection. Given this, this paper proposes an end-to-end photometric stereo multi-information fusion unsupervised anomaly detection model. First, the photometric stereo feature generator is used to obtain normal, reflectance, depth, and other information to reconstruct the 3D topographic details of the object’s surface. Second, a multi-scale channel attention mechanism is constructed to fully use the feature associations of different layers of the backbone network, and the limited feature information is used to enhance the defect characterization ability. Finally, the original image is fused with normal and depth features to find the feature variability between defects and defects, as well as between defects and background. The feature differences between the source and clone networks are utilized to achieve multi-scale detection and improve detection accuracy. In this paper, the model performance is verified on the PSAD dataset. The experimental results show that the algorithm in this paper has higher detection accuracy compared with other algorithms. Among them, the multi-scale attention mechanism and multi-information fusion input improve the detection accuracy by 2.56% and 1.57%, respectively. In addition, the ablation experiments further validate the effectiveness of the detection algorithm in this paper.

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Threshold Segmentation and Length Measurement Algorithms for Irregular Curves in Complex Backgrounds

Cited by 2 publications

References 24 publications

A Survey of Diverse Segmentation Methods in Image Processing

A Survey of Diverse Segmentation Methods in Image Processing

Photometric stereo multi-information fusion unsupervised anomaly detection algorithm

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