• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.31-56
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• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.65-69
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• 2001

Edge detection is the most important process that belongs to the first step in image recognition or vision system and can determine the efficiency valuation. The edge detection with color images is very difficult. because color images have lots of information that contain not only general information representing shape, brightness and so on but also that representing colors. In this paper, we propose architecture of universalized Color Morphological Pyramids(CMP) which is able to give effective edge detection. Image pyramid architecture is a successive image sequence whose area ratio 2$\^$-1/(ι= 1, 2, . . . ,N) after filtering and subsampling of input image. In this technique, noise removed by sequential filtering and resolution is degraded by downsampling using CMP in various color spaces. After that, new level images are constructed that apply formula using distance of neighbor vectors in close level images and detection its image.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1033-1039
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• 2012

In this paper, a simple and robust algorithm is proposed for detecting each steel plate from a image which contains several steel plates. Steel plate is characterized by line edge, so line detection is a fundamental task for analyzing and understanding of steel plate images. To detect the line edge, the proposed algorithm uses the small eigenvalue analysis. The proposed approach scans an input edge image from the top left corner to the bottom right corner with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Using the detected line edges, each plate is determined based on the directional information and the distance information of the line edges. The results of the experiments emphasize that the proposed algorithm detects each steel plate from a image effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3104-3120
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• 2017

The intelligent monitoring system has been successfully applied in many fields such as: monitoring of production lines, transportation, etc. Smart surveillance systems have been developed and proven effective in some specific areas such as monitoring of human activity, traffic, etc. Most of critical application monitoring systems involve object tracking as one of the key steps. However, task of tracking of moving object is not easy. In this paper, the authors propose a method to implement human object tracking in outdoor environment based on human features in shearlet domain. The proposed method uses shearlet transform which combines the human features with context-sensitiveness in order to improve the accuracy of human tracking. The proposed algorithm not only improves the edge accuracy, but also reduces wrong positions of the object between the frames. The authors validated the proposed method by calculating Euclidean distance and Mahalanobis distance values between centre of actual object and centre of tracked object, and it has been found that the proposed method gives better result than the other recent available methods.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.225-230
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• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. However, the necessity of long-range detect ion of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretical analyzed and the wave velocity was confirmed with experiment The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detect ion for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested and a long-range detection has been achieved at real underground water pipelines longer than 300m.

• Animal Bioscience
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• v.34 no.7
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• pp.1105-1115
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• 2021

Objective: To conserve and utilize the genetic resources of a traditional Chinese indigenous pig breed, Liangshan pig, we assessed the genetic diversity, genetic structure, and genetic distance in this study. Methods: We used 50K single nucleotide polymorphism (SNP) chip for SNP detection of 139 individuals in the Liangshan Pig Conservation Farm. Results: The genetically closed conserved population consisted of five overlapping generations, and the total effective content of the population (Ne) was 15. The whole population was divided into five boar families and one non-boar family. Among them, the effective size of each generation subpopulation continuously decreased. However, the proportion of polymorphic markers (P_N) first decreased and then increased. The average genetic distance of these 139 Liangshan pigs was 0.2823±0.0259, and the average genetic distance of the 14 boars was 0.2723±0.0384. Thus, it can be deduced that the genetic distance changed from generation to generation. In the conserved population, 983 runs of homozygosity (ROH) were detected, and the majority of ROH (80%) were within 100 Mb. The inbreeding coefficient calculated based on ROH showed an average value of 0.026 for the whole population. In addition, the inbreeding coefficient of each generation subpopulation initially increased and then decreased. In the pedigree of the whole conserved population, the error rate of paternal information was more than 11.35% while the maternal information was more than 2.13%. Conclusion: This molecular study of the population genetic structure of Liangshan pig showed loss of genetic diversity during the closed cross-generation reproduction process. It is necessary to improve the mating plan or introduce new outside blood to ensure long-term preservation of Liangshan pig.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.81-91
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• 2005

In this paper we present a novel approach for image retrieval using color and edge information. We take into account the HSI(Hue, Saturation and Intensity) color space instead of RGB space, which emphasizes more on visual perception. In our system colors in an image are clustered into a small number of representative colors. The color feature descriptor consists of the representative colors and their percentages in the image. An improved cumulative color histogram distance measure is defined for this descriptor. And also, we have developed an efficient edge detection technique as an optional feature to our retrieval system in order to surmount the weakness of color feature. During the query processing, both the features (color, edge information) could be integrated for image retrieval as well as a standalone entity, by specifying it in a certain proportion. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.784-793
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• 2012

Defects of TFT-LCD is detected by thresholding the difference image between the input image and template one because LCD panel has its inherent patterns. However, the pitch corresponding to pattern period is gradually changed according to the distance from the center of camera due to geometric distortion of camera characteristics. This paper presents a method to detect defects through comparing the pitch area with neighbor pitch areas where the perspective transform is performed with the extracted features to correct the distortion. The experimental results show that the performance of the proposed method is very effective for real data.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.53-62
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• 2011

In this paper, high-tech IT Convergence, to the development of complex technology, special technology, video object recognition technology was considered only as a smart - phone technology with the development of personal portable terminal has been developed crossroads. Technology-based detection of 3D face recognition technology that recognizes objects detected through the intelligent video recognition technology has been evolving technologies based on image recognition, face detection technology with through the development speed is booming. In this paper, based on human face recognition technology to detect the object recognition image processing technology is applied through the face recognition technology applied to the IP camera is the party of the mouth, and allowed the ability to identify and apply the human face recognition, measurement techniques applied research is suggested. Study plan: 1) face model based face tracking technology was developed and applied 2) algorithm developed by PC-based measurement of human perception through the CPU load in the face value of their basic parameters can be tracked, and 3) bilateral distance and the angle of gaze can be tracked in real time, proved effective.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.13-18
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• 2015

The mutilevel holographic data storage offers considerable advantage for capacity, since it can store more than one bit per pixel. In this paper, we search the number of codewords for each code depending on three conditions: (1) the number of levels, (2) the number of pixels in a codeword, and (3) the minimum Euclidean distance of a code. Increasing the number of levels per pixel creates more capacity, while causing more errors, by reducing the noise margin. Increasing the number of pixels in a codeword can increase the code rate, which means more capacity, but increases the complexity of the encoder/decoder of the code. Increasing the minimum distance of a code reduces the detection error, while reducing the code rate of the code. In such a fashion, a system design will always have pros and cons, but our task is to find out an effective one under the given conditions for the system requirements. Therefore, the numbers we searched can provide some guidelines for effective code design.