• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1311-1318
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• 2021

Agriculture is being damaged by harmful animals such as wild boars and water deer. It need to get permission to catch a wild boar and farmers are using a lot of methods to chase harmful animals. The methods through deep learning and image processing capture harmful animals with cameras. It is difficult to analyze harmful animals that are active at night. In this case, In this case, using deep learning by image correction can achieve a higher recognition rate.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.318-326
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• 2005

This paper presents the image feature extraction method and the image classification technique to select the harmful image flowed from the Internet by grade of image contents such as harmlessness, sex-appealing, harmfulness (nude), serious harmfulness (adult) by the characteristic of the image. In this paper, we suggest skin area detection technique to recognize whether an input image is harmful or not. We also propose the ROI detection algorithm that establishes region of interest to reduce some noise and extracts harmful degree effectively and defines the characteristics in the ROI area inside. And this paper suggests the multiple-SVM training method that creates the image classification model to select as 4 types of class defined above. This paper presents the multiple-SVM classification algorithm that categorizes harmful grade of input data with suggested classification model. We suggest the skin likelihood image made of the shape information of the skin area image and the color information of the skin ratio image specially. And we propose the image feature vector to use in the characteristic category at a course of traininB resizing the skin likelihood image. Finally, this paper presents the performance evaluation of experiment result, and proves the suitability of grading image using image feature classification algorithm.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.62-68
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• 2013

This paper proposes a method for identification of harmful video images based on the degree of harmfulness in the video content. To extract harmful candidate frames from the video effectively, we used a video color extraction method applying a projection map. The procedure for identifying the harmful video has five steps, first, extract the I-frames from the video and map them onto projection map. Next, calculate the similarity and select the potentially harmful, then identify the harmful images by comparing the similarity measurement value. The method estimates similarity between the extracted frames and normative images using the critical value of the projection map. Based on our experimental test, we propose how the harmful candidate frames are extracted and compared with normative images. The various experimental data proved that the image identification method based on the 2-dimensional projection map is superior to using the color histogram technique in harmful image detection performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.55-61
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• 2015

Today, IT technology provide convenience to many people. Smartphone era is opened, and market environment is changing rapidly. Pornography market is active by using smartphone use free internet. Many people access mobile harmful site of USA and Japan. App store of the apple has been cut off the porn service, but access block to mobile Web page is an impossible situation. In this paper, we proposed the harmful image detection method of using skin and non skin features to detect harmful image. Our proposed method can provide enough performance than previous method.

• Fisheries and Aquatic Sciences
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• v.2 no.2
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• pp.172-175
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• 1999

Relative DNA contents in some harmful algae were measured using DAPI staining and image analysis system. This method was useful to identify some morphologically similar species and isolates from harmful algal blooms (HABs). In exponential phase, Prorocentrum micans had higher relative DNA content (RD) of $1.83\pm0.52$ than any other isolates, followed by Cochlodinium polykrikoides $(1.10\pm0.46)$ Alexandrium tamarense $(0.93\pm0.32)$ Gyrodinium impudicum $(0.56\pm0.17)$, Scrippsiella trochoidea $(0.41\pm0.26)$ and P. minimum$(0.05\pm0.01)$. When they were fixed with Lugol's solution, it was difficult to d,iscern C. polykrikoides from G. impudicum under the light microscope, but the DNA contents were quite different in two species. C. polykrikoides contained about twice as much RD as G. impudicum under the same culture conditions and exponential phase. DAPI­stained DNA feature in C. polykrikodes showed concentrated in the peripheral part of the cell, but in G. impudicum showed a compact structure in the central part. Although A. tamarense and S. trochoidea were morphologically similar under the light microscope, nuclear DNA content of A. tamarense was twice as much as that of S. trochoidea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.721-723
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• 2004

As the Internet use has been spreading worldwide, illegal and harmful contents have been increasing on the Internet, which has become a very serious social problem. To prevent children form exposing themselves to such illegal and harmful contents on the Internet, harmful information protection systems have been developed. We examine component technologies of harmful information protection systems including text and image-based filtering solutions as well as url-based filtering solution. Also we examine the related trends and strategies which effectively prevent access to the harmful contents.

• Smart Media Journal
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• v.7 no.2
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• pp.34-39
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• 2018

There are many studies on red tide due to the continuous increase in damage to domestic fish and shell farms by the harmful red tide. However, there is insufficient domestic research of identifying harmful red tide algae that automatically recognizes red tide images. In this paper, we propose a red tide image classification method using deep learning based open source. To solve the problem of recognition of various images of red tide algae, the proposed method is implemented by using tensorflow framework and Google image classification model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6708-6714
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• 2015

Various types of multimedia contents have been widely spread and distributed with the Internet that is easy to use. Meanwhile, Multimedia contents can bright a social problem because juveniles can access such harmful contents easily through the Internet. This paper proposes a method to determine if an input image is harmful or not, using an neural network. The proposed method first detects a face region from an input image through MCT features. The method then extracts skin color regions using color features and obtains candidate nipple areas from the extracted skin regions. Subsequently, we determine if the input image is harmful, by filtering out non-nipple regions using the artificial neural network. Experimental results show that the proposed method can effectively determine the harmfulness of input images.

• Journal of the Korean Graphic Arts Communication Society
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• v.26 no.2
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• pp.79-89
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• 2008

Eco printing offers the perfect balance between getting all our printing jobs done without endangering the environment. It is important to realize that the printing industry is no exception to this rampant destruction of the planet's natural resources. In fact, surprisingly enough, its effect on the environment is an extremely harmful one. Like most other production operations, printing houses also produce harmful waste products that pollute the air we breathe in. They also put a great drain on precious natural resources. Printing houses emit what are known as volatile organic compounds (VOCs), caused by the use of petroleum-based inks, laminates, varnishes and adhesives. Studies show that these compounds, when inhaled, greatly increase the risk of asthma attacks. Eco printing, however, has a larger scope than is apparent. Eco printing has a dual essence. In order to understand what it is really all about, the issue of conservation is no less important than the need to stop polluting the environment.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.383-391
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• 2016

Ballast water provides stability and manoeuvrability to a ship. Foreign harmful aquatic organisms, which were transferred by ballast water, cause disturbing ecosystem. In order to minimize transference of foreign harmful aquatic organisms, IMO(International Maritime Organization) adopted the International Convention for the Control and Management of Ship's Ballast Water and Sediments in 2004. If the convention take effect, a port authority might need to check that ballast water is properly disposed of. In this paper, we propose a method of counting harmful aquatic organisms in ballast water thorough image processing. We extracted three samples from the ballast water that had been collected at Busan port in Korea. Then we made three grey-scale images from each sample as experimental data. We made a comparison between the proposed method and CellProfiler which is a well known cell-counting program based on image processing. Setting of CellProfiler is empirically chosen from the result of cell count by an expert. After finding a proper threshold for each image at which the result is similar to that of CellProfiler, we used the average value as the final threshold. Our experimental results showed that the proposed method is simple but about ten times faster than CellProfiler without loss of the output quality.