• Journal of Biosystems Engineering
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• v.39 no.4
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• pp.318-323
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• 2014

Purpose: This study was carried out to predict the growth period and fresh weight of sprouts grown in a cultivator designed to grow sprouts under optimal conditions. Methods: The temperature, light intensity, and amount of irrigation were controlled, and images of seed sprouts were acquired to predict the days of growth and weight from pixel counts of leaf area. Broccoli, clover, and radish sprouts were selected, and each sprout was cultivated in a 90-mm-diameter Petri dish under the same cultivating conditions. An image of each sprout was taken every 24 hours from the 4th day, and the whole cultivating period was 6 days, including 3 days in the dark. Images were processed by histogram inspection, binary images, image erosion, image dilation, and the overlay image process. The RGB range and ratio of leaves were adjusted to calculate the pixel counts for leaf area. Results: The correlation coefficients between the pixel count of leaf area and the growth period of sprouts were 0.91, 0.98, and 0.97 for broccoli, clover, and radish, respectively. Further, the correlation coefficients between the pixel count of leaf area and fresh weight were 0.90 for broccoli, 0.87 for clover, and 0.95 for radish. Conclusions: On the basis of these results, we suggest that the simple image acquisition system and processing algorithm can feasibly estimate the growth period and fresh weight of seed sprouts.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1115-1127
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• 2010

In order to increase the productivity in manufacturing TFT-LCD(thin film transistor-liquid crystal display), it is essential to classify defects that occur during the production and make an appropriate decision on whether the product with defects is scrapped or not. The decision mainly depends on classifying the defects accurately. In this paper, we present an effective classification method for film defects acquired in the panel production line by analyzing the intensity distribution and shape feature of the defects. We first generate a binary image for each defect by separating defect regions from background (non-defect) regions. Then, we extract various features from the defect regions such as the linearity of the defect, the intensity distribution, and the shape characteristics considering intensity, and construct a referential image database that stores those feature values. Finally, we determine the type of a defect by matching a defect image with a referential image in the database through the matching cost function between the two images. To verify the effectiveness of our method, we conducted a classification experiment using defect images acquired from real TFT-LCD production lines. Experimental results show that our method has achieved highly effective classification enough to be used in the production line.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.14-22
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• 2016

Because fuses have many parts, human error can occur during visual inspections. This paper proposes an automatic ammunition test algorithm for preventing human error during an inspection. The automatic ammunition test algorithm consists of the following three steps. First, the image input and preprocessing step is where an inspection image is rotated using an image rotation algorithm and the image is converted to a binary image. Second, the inspection step of arming determines if the ammunition is armed using Masked Template Matching algorithm, etc. Third, the inspection step of the parts determines if the parts are omitted using an image searching algorithm, etc. The arming or parts omission of the fuse are detected efficiently using the ammunition automatic test algorithm. The ammunition automatic test algorithm is expected to help improve the safety and reliability of 40 mm grenade fuse.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.4
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• pp.20-28
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• 2000

The error diffusion algorithm is good for reproducing continuous image to binary image. However the reproduction of edge characteristic is weak in power spectrum analysts of display error. In this paper, an error diffusion method which include pre-filter algorithm for edge characteristic enhancement is proposed Pre-filter algorithm is organized horizontal and vertical directional differential value and weighting function of pre-filter First, it is obtained the horizontal and vertical differential value from the peripheral pixels in original image using $3{\times}3$ Sobel operator Secondly weighting function of pre-filter is composed by function including absolute value and sign of differential value The improved Error diffusion algorithm using pre-filter, present a good result visually which edge characteristic is enhanced. The difference between orignal image and halftoning image is compared with edge-enhanced error diffusion algorithm by measuring the radially averaged power spectrum density.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.136-144
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• 2010

Two types of informations are used for content-based video copy detection: spatial information and temporal information. The spatial information means content-based image fingerprint. This image fingerprint must have following characteristic. First, Extraction is simple. Second, pairwise independence for random selected two images. At last, Robust for modifications. This paper proposed image fingerprint method for contents based video copy detection. Proposed method's extraction speed is fast because this method's using block average, first order differentiation and second order differentiation that can be calculated add and minus operation. And it has pairwise independence and robust against modifications. Also, proposed method feature makes binary by comparisons and using coarse to fine structure, so it's matching speed is fast. Proposed method is verified by modified image that modified by VCE7's experimental conditions in MPEG7.

• Journal of the Korean Ceramic Society
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• v.39 no.8
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• pp.735-741
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• 2002

This paper investigates circularity of fly ashes using the digital image processing. Fly ashes directly collect from electrostatic precipitator when the load of conditions of boiler are changed at a coal-fired power plant. Circularity measurement can be accomplished in five steps: ① image acquisition, ② grey image processing, ③ detection the component to measure ④ binary image processing ⑤ feature measurement. The mean circularity of fly ashes is in the range of 0.78 to 0.83. fly ashes collected from the same hopper has similar circularity regardless of the load of boiler and circularity increases as going from the 1st hopper to 3rd one, namely as particle size become finer.

• Journal of Biosystems Engineering
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• v.19 no.2
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.59-65
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• 2012

Hot pepper can be easily faded or discolored in drying process, so we need to use the sorting technique to improve the quality for dried hot pepper. Independent Component Analysis (ICA) is one of the most widely used methods for blind source separation. In this paper we use this technique to get a concentration image of the most important component which plays a role in the dried pepper. This concentration image is different from the binary image and it reflects the characteristics of major components, so that we know the distribution and quality of the component and how to sort the dried pepper. Also, the size of the concentration image can tell the relation with capsaicinoids which make hot taste. We propose a sorting method of the dried hot pepper that is faded or discolored and lacked a major component likes capsaicin in drying process using ICA concentration image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.598-601
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• 2002

In this research, robustness of image watermarking mixed Key and Logo scheme was evaluated. A personal ID of a copyrighter was key and watermark was logo image. The standard images of Baboon, Cameraman and Lena were used for experimental images, binary image‘Park’of 32$\times$32 and 64$\times$64 size were used for the watermark image, respectively. for robustness evaluation of the watermark, reconstructive rates of the watermark were obtained from images inserted watermark with image transformation or JPEG lossy compression. The experimental results show that the reconstructive rates of the case of 32$\times$32 watermark was better than the case of the 64$\times$64 watermark; average 5.9%, 13.9%, 6.5%, and 4.2% in the case of scale-down rates, rotational rates, impulse noise power density, and JPEG lossy compression rates, respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.1
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• pp.37-43
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• 2001

In this paper, we propose a new optical security technique using two phase masks based on interferometer. A binary random phase image is used as a reference image and the encrypted image is generated according to the phase difference between the reference image and the original image. If there is no phase difference of a same pixel position in two phase masks, interference intensity of the pixel has minimum value and if phase difference of a same pixel position in two phase masks is $\pi$, its interference intensity has maximum value. We can decrypt the original image by putting two phase masks on each of the two optical paths of the Mach-Zehnder interferometer. Computer simulation and the optical experiments show a good performance of the proposed optical security system.