Autofocus method based on multi regions of interest window for cervical smear images

Zhang, Chuanwang; Jia, Dongfang; Wu, Nengkai; Guo, Zhigang; Ge, Hairui

doi:10.1007/s11042-022-12247-x

Cited by 3 publications

(3 citation statements)

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“…At present, auto-focus technology can be divided into two categories: passive autofocus (PAF) [8][9][10][11][12][13] and active auto-focus (AAF) [14][15][16][17][18][19][20][21]. The PAFs mainly rely on image processing algorithms to evaluate the image definition and predict the defocus amount by referring to the definition value, which does not require additional light sources and auxiliary optical paths.…”

Section: Introductionmentioning

confidence: 99%

“…In 2021, D. Peter proposed a search algorithm based on the Gaussian standard deviation and gradient block [12]. In 2022, C. Zhang proposed an auto-focus method based on a multi-interesting area window, which applied multiple medium-value filtering and the accuracy of the right to noise to improve the noise improvement [13]. Due to the advantage of low cost, PAFs are widely used in many industries.…”

Section: Introductionmentioning

confidence: 99%

“…Due to the advantage of low cost, PAFs are widely used in many industries. However, the analysis of the image is complex and too many iterations are needed, which makes it hard to meet the precision and real-time requirements for the Micro-LED wafer defects detection [12,13]. In contrast, the AAFs require additional light sources (mostly a laser) and specially designed optical paths.…”

Section: Introductionmentioning

confidence: 99%

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Rectangular Amplitude Mask-Based Auto-Focus Method with a Large Range and High Precision for a Micro-LED Wafer Defects Detection System

He,

Ma,

Wang

2023

Sensors

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Auto-focus technology plays an important role in the Micro-LED wafer defects detection system. How to accurately measure the defocus amount and the defocus direction of the Micro-LED wafer sample in a large linear range is one of the keys to realizing wafer defects detection. In this paper, a large range and high-precision auto-focus method based on a rectangular amplitude mask is proposed. A rectangular amplitude mask without a long edge is used to modulate the shape of the incident laser beams so that the spot shape distribution of the reflected laser beam on the sensor changes with the defocus amount of the wafer sample. By calculating the shape of the light spots, the defocus amount and the defocus direction can be obtained at the same time. The experimental results show that under the 20× microscopy objective, the linear range of the auto-focus system is 480 μm and the accuracy can reach 1 μm. It can be seen that the automatic focusing method proposed in this paper has the advantages of large linear range, high accuracy, and compact structure, which can meet the requirements of the Micro-LED wafer defects detection equipment.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Rectangular Amplitude Mask-Based Auto-Focus Method with a Large Range and High Precision for a Micro-LED Wafer Defects Detection System

He,

Ma,

Wang

2023

Sensors

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Analysis and comparison of automatic image focusing algorithms in digital image processing

Zhou,

Yang

2023

Journal of Radiation Research and Applied Sciences

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Maximum Gradient Autofocus Technology of Microsporidia Images Based on Color Feature

Xiong

Bai³

et al. 2023

Int. J. Patt. Recogn. Artif. Intell.

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There are many impurities in the microscopic images of extracted microsporidia samples of Bombyx mori pebrine, and Bombyx mori pebrine with elliptical symmetric shape has certain fluidity and obvious stratification. Traditional focusing methods cannot accurately locate the main regions of microsporidia images, and the focusing effect is poor. On this basis, an automatic focusing method combining the microsporidia image features and the evaluation and determination of maximum gradient direction is proposed. First, the HSV color space with stable color information is used to extract the suspected positions of microsporidia targets, so that the interference of some impurities under complex backgrounds is removed and the redundancy of image content calculation is reduced. Then, combined with the light green features of Bombyx mori pebrine, the G-component gray image of microsporidia in the RGB color space is used to extract the significant gradient region. A dynamic focus window is constructed to accurately locate the target region and reduce the influence of microsporidia flow on the focus evaluation function and the bimodal interference caused by impurities. Finally, the maximum second-order difference is obtained through the four-dimensional gradient distribution, and the focus sharpness evaluation function is formulated to adapt to the microsporidia shape and improve the sensitivity of the focus function. The experiments show that under the dynamic window of microsporidia color gradient of different samples, the sharpness ratio and the highest sensitivity factor of the focus evaluation function proposed in this paper can reach 0.06341 and 0.95, respectively. It can meet the accurate and sensitive autofocus of microscopic images of color microsporidia samples under complex backgrounds.

show abstract

Autofocus method based on multi regions of interest window for cervical smear images

Cited by 3 publications

References 50 publications

Rectangular Amplitude Mask-Based Auto-Focus Method with a Large Range and High Precision for a Micro-LED Wafer Defects Detection System

Rectangular Amplitude Mask-Based Auto-Focus Method with a Large Range and High Precision for a Micro-LED Wafer Defects Detection System

Analysis and comparison of automatic image focusing algorithms in digital image processing

Maximum Gradient Autofocus Technology of Microsporidia Images Based on Color Feature

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