Presentations -
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Object Tracking Based on Color Features from Key Frames International conference
Mie Mie Tin, Mie Mie Khin, Nyein Nyein Myo, Thi Thi Zin, Pyke Tin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
In the world, everybody needs to protect their life to save and to prevent from dangerous case. Some case cannot protect for life, such as accident case on the road, the criminal case and so on. It says that need to give some information to them that is never emancipate from the criminal case and never find bolt-hold. This system can support like case, because system processes under the security surveillance camera network and use all video files from that camera network. These videos are extracted as frames based on time and relevant frames are stored as frame sequence. The system extracts key information frames from that frames sequence with relevant time. The system handles all important key information frames and extract important object using colour features base and collects the path of that object by tracking of different background region. To track selected object, the system collects all key information frames from videos in a network with time base. The selected importance key object is searched other information key frames. To search selected object from other key frames, the system use object segmentation on colour features.
The user needs to select tracking objects from key frames a video. That selected important object is extracted feature values based on RGB features and HSV hue value. This research tests on private dataset, surveillance camera network, from Myanmar Institute of Information Technology University (MIIT), Mandalay, Myanmar. All surveillance cameras are configured at the different stable places and camera view is stable in vision. That camera network has 85 cameras totally and used HIKVISION network bullet camera and HIKVISION E series Network Speed Dome camera. This research is ongoing stage and five members are working as a group. -
An Algebraic Geometric Imaging Approach for Automatic Dairy Cow Body Condition Scoring System International conference
Thi Thi Zin, Pyke Tin, I. Kobayashi, and Y. Horii
2019 International Conference on Precision Dairy Farming Technologies and Applications (Tokyo, Japan) World Academy of Science, Engineering and Technology
Event date： 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Tokyo, Japan
In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.
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Multivariate Stochastic Analyzer for Dairy Cow Body Condition Scoring International conference
Thi Thi Zin, K. Sumi, Pyke Tin
International Conference on Digital Image and Signal Processing (DISP 2019) (Oxford University, UK)
Event date： 2019.4.29 - 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Oxford University, UK
In this paper, we introduce a conceptual multivariate stochastic analyzer for assessing body condition scores of individual dairy cows. Specifically, by using digital image technologies and statistical stochastic methods, dairy cow body condition scoring machine is to be established. In modern precision dairy farming, the body condition score (BCS) plays an important role as an indicator for measuring health and wealth of a dairy farm. Based on the BCS, today dairy farm manage systems are improved in in various aspects such as milk production, right time for artificial insemination, prediction calving time and so on. Traditionally, human experts perform visual examinations on the key areas of cow body parts such as hook, pin bones, tail head, short ribs, and backbone starches for scoring. However, well-trained human experts become less and dairy farm sizes are bigger as a consequence manual body condition scoring is almost impractical. Thus, in this paper we propose an image technology based stochastic analyzer for automatic scoring the BCS measures of dairy cows. In order to do so, the proposed analyzer first extracts some key anatomical points of a cow by using two-dimensional images taken from top views. Then, the system will derive some distance and angular features of the anatomical points and employs stochastic sampling techniques for refining the extracted features to produce parameters of multiple regressive prediction models and to assess the body condition scores of all dairy cows in the farm. Finally, to confirm the validity of proposed analyzer, we perform some experiments by a well-known benchmark dataset. The experimental results seem to be promising with an impact of high accuracy.
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Incorporating Digital Imaging in Dairy Cow Anatomical Feature Detection International conference
Thi Thi Zin, Cho Nilar Phyo, Pyke Tin
International Conference on Digital Image and Signal Processing (DISP 2019) (Oxford University, UK)
Event date： 2019.4.29 - 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Oxford University, UK
In today precision dairy farming, the most commonly used technologies include wearable devices which must be attached to cows in one way or another in order to monitor cow’s behaviors. Since the wearable sensors placements may be broken or lost and can burden additional stress to the cows, it is necessary to consider an alternative and effective non-contact monitoring system. For this purpose, digital imaging technologies are suitable due to their capabilities of continuous operation and able to full automation. Thus, in this paper, we propose a digital imaging approach based on topological persistence concepts to precision dairy cow monitoring system focused on automated dairy cow anatomical feature detection. Anatomically these features define as hips, hooks, pin bones, tail-heads and rear regions of the cow body. These features will be utilized in the decision making process if and where a cow is present in an image or video frame. Once the system detects a cow in the image, the system automatically identifies an individual cow. The proposed cow anatomical feature detection and cow identification have the potentials in detecting cow body conditions, health conditions in time, milk production trends and predicting calving time and heat occurrence. Finally, by using videos taken in a real-life cow farm, the experimental results confirm the validity of proposed method.
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Dairy Cow Body Conditions Scoring System Based on Image Geometric Properties International conference
Thi Thi Zin, Pyke Tin, Ikuo Kobayashi
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
In modernized precision dairy farming, the importance of dairy cow body condition scores is well recognized for making the healthy, wealthy and optimizing milk production. Although a burst amount of researches have been investigated the condition scoring problems from various aspects, not much satisfactory results have been come out yet. So, this paper will propose a geometric imaging approach for an automatic dairy cow body conditions scoring system. Specifically, some significant land marks or anatomical points are to be extracted from the top view image of a cow and their geometrical properties such as angles, length and area are investigated to estimate body condition scores. In doing so, the proposed method will employ techniques of polynomial regression, multiple regression, Markov Chain classification. Finally, some experimental results will be presented by using self-collected datasets and some well-known public datasets. The performance of preliminary results shows promising so that the approach of proposed method can lead to be applicable in real life environments.
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OCR Perspectives in Mobile Teaching and Learning for Early School Years in Basic Education International conference
Thi Thi Zin, Swe Zar Maw, Pyke Tin
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
In these days, teaching and learning systems in schools with the use of mobile or portable devices such as tablets, e-readers, smartphones are becoming keen interests of educators as well as parents and teachers in worldwide. In this aspect, the early years of school children in basic education are the most challenging and important in developing effective and quality education for life. Since they are quite young and unable to dedicate time the need for easy to use and effective learning aids has become vital. Especially their writing skills are somehow needed to be improved with encouragements. In order to do so, the handwritten of characters and numerals performed by the children especially those living in less developing countries should be correctly recognized so that means and ways for remedies and solutions for improvements could be found. Thus the optical character recognition techniques for handwritten alphabets and numerals are moving into front especially the handwritten of children of early years in schools. In this paper, we introduce a Mobile Tutor - an effective and correct way of character segmentation and recognition of messy and unclear handwritten characters to help children learn and practice handwriting and early numeric operations such as addition and subtraction as well as help teachers monitor and review children’s progress. Some experiments are performed by providing tablets to the users and collecting handwritten characters from the users for recognition and analysis.
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A Study on Detection of Precursor Behaviors of Estrus in Cattle Using Video Camera International conference
Hiromitsu Hama, Tetsuya Hirata, Tsubasa Mizobuchi, Thi Thi Zin
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
Development of an estrus detection system by non-contact and non-invasive methods to improve productivity is a strong desire from livestock farmers with aging society. As one of the elemental technologies, we will focus on detecting precursor behaviors of estrus in cattle using video camera. First, we converted from two-dimensional motion on video image to three dimensional one. Next, some features which are well-known as estrus precursor behaviors, were selected, for example, walking speed, trajectory and relative positional relationship of two cattle. Through experimental results, we could confirm the effectiveness of our proposed algorism. As the result, although it is a small case, it was able to detect without any false positive and false negative.
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Innovations of Digital Imaging in Smart Dairy Farming Invited International conference
Thi Thi Zin
The 17th International Conference on Computer Applications (ICCA 2019) and The 11th International Conference on Future Computer and Communication (ICFCC 2019) (Novotel Hotel, Yangon, Myanmar) University of Computer Studies, Yangon
Event date： 2019.2.27 - 2019.3.1
Language：English Presentation type：Oral presentation (invited, special)
Venue：Novotel Hotel, Yangon, Myanmar
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Framework of Cow Calving Monitoring System Using a Single Depth Camera International conference
K. Sumi, Thi Thi Zin, I. Kobayashi, Y. Horii
International Conference Image and Vision Computing New Zealand (IVCNZ 2018) (Auckland, New Zealand) IEEE Advancing Technology for Humanity (Technically co-sponsor)
Event date： 2018.11.19 - 2018.11.21
Language：English Presentation type：Poster presentation
Venue：Auckland, New Zealand
Calving difficulty is the primary cause of the problem of increasing death loss in cow-calf. It also profoundly effects on the economic impact of farmers and producers because of calves' death, injury to cows and high veterinary cost. To help the calving difficult of cows in time, long time continuous monitoring is required for deciding when and how to assist the calving process of cows. On the other hand, the continuous monitoring of cows' welfare become the major burden task for labors especially in a large farm where has a large number of cows. Therefore, the demands of sophisticated technology for automatic monitoring of cows' welfare is more and more increasing every year. In recent years, some researcher develops the automatics monitoring and predicting the cows' calving behavior by using the sensors devices such as temperature sensors and acceleration sensors. However, the sensors based system has various problems such as spalling and malfunction of the sensors and even can cause the burden on the cow because sensors are needed to put inside or on the body of the cow. To overcome those problems, in this paper, we propose an automatic detection of cows' calving behavior by using the depth camera (3D camera) along with image processing and computer vision technology and coordinate system transformation concept. The proposed system by using 3D camera can reduce the burden of both labors and cows.
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A Hybrid Rolling Skew Histogram-Neural Network Approach to Dairy Cow Identification System International conference
Cho Nilar Phyo, Thi Thi Zin, H. Hama, I. Kobayashi
International Conference Image and Vision Computing New Zealand (IVCNZ 2018) (Auckland, New Zealand) IEEE Advancing Technology for Humanity (Technically co-sponsor)
Event date： 2018.11.19 - 2018.11.21
Language：English Presentation type：Poster presentation
Venue：Auckland, New Zealand
In this paper, we propose a hybrid method in which rolling skew histogram and neural network techniques are fused to recognize patterns and identify cows in the milking rotary parlor of dairy farms. Individual cow identification is very important for managing the welfare and health care of an individual cow and developing the body condition scoring system. Although there has some sensor-based cows' identification system, those systems require to attach the sensor devices on each cow which is costly and burden on the cows. Since the proposed method applies a single video camera which is a non-contact device for the identification of many different cow patterns, the proposed system is low cost and no burdens on the cow. In particular, the operation of the system takes place while the cows are in the milking process in rotary milking parlor where the monitoring of individual cow is more effective than some other time and places. The identification process is based on the black and white pattern on the cow's body while moving on the rotary milking parlor. For the detecting and cropping of cows' body region is carried out by using rolling the skew histogram and used for the training process of the deep convolutional neural network. The trained network is employed for the identification of individual cow in the testing process. The experiments are performed on the self-collected cow video dataset which includes around 60 different cow's body patterns that have been taken at the large-scale farm in Oita Prefecture, Japan. The experimental results show that the proposed system is promising with the overall accuracy of 96.3 % and it is very effective and practical for the real-time cow identification system needed for establishing a modern precision dairy farming.
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An Image Technology Approach to Dairy Cow Monitoring System Invited International conference
Thi Thi Zin
National Symposium on Livestock Research and Development 2018, The Faculty of Animal Science, Universitas Gadjah Mada (Universitas Gadjah Mada, Yogyakarta, Indonesia) The Faculty of Animal Science, Universitas Gadjah Mada
Event date： 2018.11.5
Language：English Presentation type：Oral presentation (invited, special)
Venue：Universitas Gadjah Mada, Yogyakarta, Indonesia
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ICTを活用した牛のモニタリングシステムの開発に関する研究 Invited
Thi Thi Zin, 小林 郁雄、椎屋 和久、PYKE TIN、堀井 洋一郎、濱 裕光
九州ＩＣＴイノベーションセミナー2018 (アクロス福岡) 総務省九州総合通信局、（一社）九州テレコム振興センター（KIAI）
Event date： 2018.11.2
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：アクロス福岡
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暮らしを快適に変える画像処理技術 Invited
Thi Thi Zin
Yumenavi LIVE 2018、学問の講義ライブ (マリンメッセ福岡) FROMPAGE
Event date： 2018.10.20
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：マリンメッセ福岡
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A Study on Abnormal Behavior Detection of Infected Shrimp International conference
Takehiro Morimoto, Thi Thi Zin, Toshiaki Itami
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
A method of detecting infected shrimp has been developed. Though shrimp production is thriving in Japan, disease causes much damage. Because the cause is a virus infection, medical treatment is not currently possible. The infection route includes factors such as predation by environmental organisms and water-borne infection. However, no specific countermeasures have been developed. Therefore, early detection of infected shrimp is necessary to prevent secondary infection. When shrimp are infected, they exhibit the following abnormal behaviors: 1) not eating, 2) appearing in shallow water, or 3) making sudden movements. The developed method of detecting infected shrimp involves the use of image processing to determine when the shrimp are not eating.
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A Study on Non-contact and Non-invasive Neonatal Jaundice Detection and Bilirubin Value Prediction International conference
Sojiro Kawano, Thi Thi Zin, Yuki Kodama
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
Neonatal jaundice is a yellowish discoloration of skin and eyes that commonly occurs in newborn babies. It is a physiological phenomenon in neonates and it occurs due to the overproduction of bilirubin, reduction of bilirubin treatment function. The quick and accurate treatment is required for neonatal jaundice because it can lead to nuclear jaundice, cerebral palsy, intellectual disturbance and various sequelae. The investigation methods for examining neonatal jaundice include examination using jaundice meter and blood sampling. However, these methods require continuous monitoring and can cause burden on newborn babies. In this paper, we propose the non-contact and non-invasive detection method for neonatal jaundice using image processing and computer vision technology. The experiments are performed on the data collected by University Hospital, University of Miyazaki. According to the experiments, we confirmed about the usefulness of proposed method which can work effectively for infants.
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An Automatic Estimation of Dairy Cow Body Condition Score Using Analytic Geometric Image Features International conference
Thi Thi Zin, Pyke Tin, I. Kobayashi, Y. Horii
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
In today modern precision dairy farms, among many dominant factors the Body Condition Score (BCS) has been considered a critical value to optimize milk production, analyzing health problems, insemination timing, and many others. Currently, the BCS is measured by human experts giving time- consuming and varying outcomes from one expert to another so that an automatic estimation system for body condition scoring is needed to be developed. Although there have been some researchers on the topics of the BCS by using image processing techniques, an efficient and satisfactory method has not been found yet. Therefore, in this paper, a new approach to an automatic estimation of dairy cow BCS using analytic geometry image features will be considered. Some experimental results are shown by using the BCS database.
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A Study on Detection and Tracking of Estrous Behaviors for Cattle Using Laser Range Sensor and Video Camera International conference
Tsubasa Mizobuchi, Thi Thi Zin, Ikuo Kobayashi, Hiromitsu Hama
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
Nowadays, the methodology of cattle production has been transferred from natural mating to artificial insemination. Therefore, estrous detection for cattle is very important to determine the time period that farmers conduct artificial insemination. However, the observation of estrous behavior by human's eyes through the whole day become as a burden task when the number of cattle is large. Therefore, most farmers are missing to notice estrous behavior. In this paper, we proposed the method for automated detection of cattle's estrous behavior, which is mounting and standing, by using laser range sensor and image processing technology. Some experiments are carried out at the Sumiyoshi field, Faculty of Agriculture, University of Miyazaki. Through experimental results, the effectiveness of our proposed method was confirmed.
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Medication and Meal Intake Monitoring using Human-Object Interaction International conference
Pann Thinzar Seint, Thi Thi Zin, Mitsuhiro Yokota
2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018) (Nara Royal Hotel, Nara, Japan) IEEE Consumer Electronics Society
Event date： 2018.10.9 - 2018.10.12
Language：English Presentation type：Oral presentation (general)
Venue：Nara Royal Hotel, Nara, Japan
Needs for end-of-life care are rising because of increasing age-related challenges. Among them, maintenance of nutrition and medication play an important role in healthcare of elderly people. In this situation, caregivers need to receive the daily record as a trending of usage which will lead to improvements in the quality of care. Our objective is to establish a video monitoring system for the act of taking medication and eating activity which is designed by using human-object interaction. For the evaluation of medication intake scenario, we propose the hierarchical classification system using hybrid PRNN-SVM model for action classification and activity interpretation. By the contribution of rulebased learning, our system also recognizes drinking/eating activity.
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最新の画像処理技術と畜産およびセキュリティシステムへの応用 Invited International conference
Thi Thi Zin
The 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018) (シーガイアコンベンションセンター (Miyazaki, Japan)) IEEE SMC Society
Event date： 2018.10.7 - 2018.10.10
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：シーガイアコンベンションセンター (Miyazaki, Japan)
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暮らしを快適に変える画像処理技術の進歩 Invited
Thi Thi Zin
第２回理系女子支援講座、宮崎県立宮崎北高等学校 (宮崎県立宮崎北高等学校) 宮崎県立宮崎北高等学校
Event date： 2018.9.8
Language：Japanese Presentation type：Oral presentation (invited, special)
Venue：宮崎県立宮崎北高等学校