• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.935-938
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• 1998

In this paper, we propose a new auto focus algorithm using variance which estimate spread characteristic of image. In the proposed algorithm, the focus value is calculated via variance of difference between two adjacent pixels. This algorithm, we propose, show much more sharp focus curve than any other algorithms. It is shown experimentally that the proposed auto focus algorithm can be a efficient alternative to existing Tenengrad-based auto focusing algorithms.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.9
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• pp.447-453
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• 2001

In this paper, a new auto-focusing algorithm for digital cameras is proposed. One of the primary concerns of digital image processing is to increase image quality, and the most important factor for degrading the images is the blurring effect due to inexact focusing. The blurring effect occurs when the focusing lens is located on an unsuitable position. Therefore, focusing on an object should be proceeded before acquiring images. The proposed auto-focusing algorithm is MMDT(min-max difference threshold), and the performance of the proposed algorithm is evaluated by the use of the focus curve. It is shown that the proposed algorithm is superior to other previous auto-focusing algorithms in both the focus shape and computation time aspects. Especially, the improvement of the focus curve shape in both monotonousness and slope indicates that focusing can be done rapidly in comparison with other previous proposed algorithms.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.585-594
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• 2006

Due to the size limit, the voice coil motor (VCM) is adopted in most of the mobile phone camera to control auto-focus instead of step motor. The optical system using the VCM has the property that the focus values are varying even though the same current is induced. It means that an error of the lens position was taken placed due to the characteristics of the VCM. In this paper, a algorithm was proposed to compensate the lens position error using the step size and the search count of each stage. In the proposed algorithm -7 step middle searching stage is inserted the conventional searching algorithm for the fast auto-focus searching and the final searing step size was set to +1 for the precise focus control, respectively. In the experimental results, the focus values was found more fast in the proposed algorithm than the conventional. And more the image quality by the proposed algorithm was superior to that of the conventional.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.3 s.357
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• pp.12-19
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• 2007

This paper proposes the enhanced auto-focus algorithm detecting several objects and selecting the target object. Proposed algorithm first detects some objects distributed in the image using focus measure operator and multi-window and then selects the target object through fuzzy reasoning with three fuzzy membership functions. Implementation can be simple because it only needs image sensor instead of infrared or ultrasonic equipment. Experimental result shows that the proposed algorithm can improve the quality of image by focusing to the target object.

• Journal of KIISE:Software and Applications
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• v.32 no.9
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• pp.878-887
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• 2005

The passive focusing method finds the in-focus position by analyzing images captured by a camera. In this paper, we propose an efficient passive auto-focusing algorithm for video measuring systems. The sum of modified Laplacian of Gaussian is used to calculate focus values from images and Gaussian curve fitting is applied to estimate the optimal in-focus position. The Proposed method is tested for various objects and illuminations. The test result is compared with other methods to verify accuracy and efficiency of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1003-1006
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• 2005

Demand of Auto Focus for Camera module is increased very fast in these days and will be adapted to most of mobile phones in next few years instead of traditional method, fixed focus. To make auto focus function, 2 kinds of solutions, VCM(Voice Coil Motor) and Piezo linear motor are normally used. In this paper, VCM which commercially strong candidate for Auto focus mechanism was investigated to verify principles are match up to the actual operation. Auto focus algorithm is different between 1 chip and 2 chip solution. Normally 2 chip is more complicate than the other. To have best performance on this function, hysteresis and depth of field(DOF) table should be optimized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.320-323
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• 2011

The compact camera assembled into Smart phone is required to have higher resolution level in non AF state than existing handsets, and it is also requested to have higher degree of accuracy, more consistent repetitiveness, and faster auto focusing speed. Algorithm based on a mechanical position of the existing actuator has been discussed. Therefore, in this thesis I suggest an improved algorithm concerning the problem of unstable resolution level in non AF state and auto focusing speed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.7
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• pp.313-318
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• 2006

An automatic sample centering system is underway at the protein crystallography beam line of the Pohang Light Source to improve the efficiency of the crystal screening process. A sample pin which contains a protein crystal is mounted on a goniometer head. Then the crystal should be moved to the center of X-ray beam by controlling the motorized goniometer to obtain diffraction data. Since the X-ray beam is located at the center of the image obtained from the CCD camera when the image of the sample pin is in focus, an auto-focusing algorithm is a very important part in the auto-sample-centering system. However the results of applying several well-known auto focusing algorithms directly to the images are not satisfactory owing to the following factors: misalignment of CCD camera, non-uniform cryo-stream in the background of the image and the supporter of the loop. The performance of an auto-focusing algorithm can be increased if the algorithm is applied to only the loop region identified. Non-uniform cryo-stream and a various illumination condition and a stain, which is shown in the image, are main obstacles to loop region identification. In this paper, a simple loop region identification algorithm, which can solve these problems, is proposed and the effective ness of the proposed scheme is shown by applying the auto-focusing algorithm to the loop region identified.

• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.159-165
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• 2012

The accurate focusing position should be determined for accurate measurements In VMS. Camera lens focusing is an important problem in computer vision and video measuring systems (VMS) that use CCD cameras and high precision XYZ stages. Camera focusing is a very important step in high precision measurement systems that use computer vision technique. The auto focusing process consists of two steps, the focus value measurement step and the exact focusing position determination step. It is suitable for eliminating high frequency noises with lower processing time and without blurring. An automatic focusing technique is applied to measure a crater with a one-dimensional search algorithm for finding the best focus. Throughout this paper, the suggested algorithm for the Auto focusing was combined with the learning. As a result, it is expected that such a combination would be expanded into the system of recognizing voices in a noisy environment.