• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.151-160
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• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.8
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• pp.1194-1198
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• 2005

A computer vision system was designed and validated to recognize an individual Holstein cattle by processing images of their body patterns. This system involves image capture, image pre-processing, algorithm processing, and an artificial neural network recognition algorithm. Optimum management of individuals is one of the most important factors in keeping cattle healthy and productive. In this study, an image-processing system was used to recognize individual Holstein cattle by identifying the body-pattern images captured by a charge-coupled device (CCD). A recognition system was developed and applied to acquire images of 49 cattles. The pixel values of the body images were transformed into input data comprising binary signals for the neural network. Images of the 49 cattle were analyzed to learn input layer elements, and ten cattles were used to verify the output layer elements in the neural network by using an individual recognition program. The system proved to be reliable for the individual recognition of cattles in natural light.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1097-1100
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• 2005

A choice of a term represent the contents of the documents should be preceded in recognition of the name of an individual. The recognition of the name of an individual which has high reliability can raise the building of information extract system into higher level. Up to now active research on the recognition of the name of an individual human name and the general recognition of the name of an individual have been studied, detailed research on the recognition of the name of a place hasn't be done, however. This thesis suggests detailed methods of recognition of Korean place names system with applying a rule made manully.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.213-217
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• 2008

This paper proposes a novel method for the recognition of passports based on the CDM(Conditional Dilation Morphology) masking and the ART2-based RBF neural networks. For the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an ART2-based hybrid network that adapts the ART2 network for the middle layer. This network is applied to the recognition of individual codes. The experiment results showed that the proposed method has superior in performance in the recognition of passport.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.1088-1092
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• 2002

This paper introduces that domestic animals can be effectively administered with an individual recognition system. The system was constructed in original code transmitter, receiver, personal computer, micro-processor, and RS485 telecommunications module. In the individual recognition system. the signal including encoded information about a milk-cow was transmitted from an original code transmitter to a micro-processor through RS485 telecommunications module. The transmitted signal was successfully displayed in a personal computer.

• The Korean Journal of Ecology
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• v.25 no.6
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• pp.365-369
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• 2002

We had 18 eggs artificially hatched in a mass breeding place of black-tailed gulls and examined the individual recognition between young siblings in a laboratory environment. The results of the experiment showed that the young gulls selectively responded to their siblings and non-siblings at an early stage after hatching. It was shown that they began to recognize the begging call among the voice signals of siblings and non-siblings 15-16 days after hatching, and the chirirah call 11-12 days after hatching. Also, more significant results were shown with the chirirah call than with the begging call. In an experiment of visual recognition between siblings and non-siblings, the young black-tailed gulls approached their siblings significantly 9-10 days after hatching. The recognition between young siblings in a mass breeding place provides an important evolutionary indicator in terms of their social behaviors.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.1-8
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• 2020

Recent studies revealed that many animals identify individual humans. In this account, we review previous literatures on individual human recognition by wild or domestic animals and discuss the three hypotheses: "high cognitive abilities" hypothesis, "close human contact" and "pre-exposure to stimuli" hypothesis. The three hypotheses are not mutually exclusive. Close human contact hypothesis is an ultimate explanation for adaptive benefits whereas high cognitive abilities and pre-exposure to stimuli hypothesis are proximate explanations for mechanisms to perform such discriminatory behaviour. We report a case study of two bird species in a human-free habitat. Long-tailed skuas, which are known for having high cognitive abilities, exhibited the human discriminatory abilities whereas ruddy turnstones did not display such abilities toward approaching humans. This suggests that highly intelligent species may have this type of discriminatory ability so that they could learn to identify individual humans quickly by pre-exposure to stimuli, even in a human-free habitat. Here, we discuss that human recognition is more common in species with rapid learning ability and it could develop for a short period of time between an intelligent species and human.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.77-85
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• 2009

In this paper, we propose data format for smell, taste, touch with speech and vision which can be transmitted and implement a floral scent detection and recognition system. We provide representation method of data of smell, taste, and touch. Also, proposed floral scent recognition system consists of three module such as floral scent acquisition module using Metal Oxide Semiconductor (MOS) sensor array, entropy-based floral scent detection module, and floral scent recognition module using correlation coefficients. The proposed system calculates correlation coefficients of the individual sensor between feature vector(16 sensors) from floral scent input point until the stable region and 12 types of reference models. Then, this system selects the floral scent with the maximum similarity to the calculated average of individual correlation coefficients. To evaluate the floral scent recognition system using correlation coefficients, we implemented an individual floral scent recognition system using K-NN with PCA and LDA that are generally used in conventional electronic noses. In the experimental results, the proposed system performs approximately 95.7% average recognition rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.196-212
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• 2014

Facial expression recognition is an important part in emotional interaction between human and machine. This paper proposes a facial expression recognition approach based on multi-classifier fusion with stacking algorithm. The kappa-error diagram is employed in base-level classifiers selection, which gains insights about which individual classifier has the better recognition performance and how diverse among them to help improve the recognition accuracy rate by fusing the complementary functions. In order to avoid the influence of the chance factor caused by guessing in algorithm evaluation and get more reliable awareness of algorithm performance, kappa and informedness besides accuracy are utilized as measure criteria in the comparison experiments. To verify the effectiveness of our approach, two public databases are used in the experiments. The experiment results show that compared with individual classifier and two other typical ensemble methods, our proposed stacked ensemble system does recognize facial expression more accurately with less standard deviation. It overcomes the individual classifier's bias and achieves more reliable recognition results.

• Speech Sciences
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• v.9 no.4
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• pp.253-263
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• 2002

In this paper, we propose new algorithm of speaker recognition which identifies the speaker using the information obtained by the intensive speech feature analysis such as pitch, intensity, duration, and formant, which are crucial parameters of individual voice, for candidates of high percentage of wrong recognition in the existing speaker recognition algorithm. For testing the power of discrimination of individual parameter, DTW (Dynamic Time Warping) is used. We newly set the range of threshold which affects the power of discrimination in speech verification such that the candidates in the new range of threshold are finally discriminated in the next stage of sound parameter analysis. In the speaker verification test by using voice DB which consists of secret words of 25 males and 25 females of 8 kHz 16 bit, the algorithm we propose shows about 1% of performance improvement to the existing algorithm.