• International journal of advanced smart convergence
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• v.9 no.3
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• pp.85-96
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• 2020

It is important to extract salient object image and to solve the invariance problem for image recognition. In this paper we propose a new hybrid algorithm for invariance and improved classification performance in image recognition, whose algorithm is combined by FT(Frequency-tuned Salient Region Detection) algorithm, Guided filter, Zernike moments, and a simple artificial neural network (Multi-layer Perceptron). The conventional FT algorithm is used to extract initial salient object image, the guided filtering to preserve edge details, Zernike moments to solve invariance problem, and a classification to recognize the extracted image. For guided filtering, guided filter is used, and Multi-layer Perceptron which is a simple artificial neural networks is introduced for classification. Experimental results show that this algorithm can achieve a superior performance in the process of extracting salient object image and invariant moment feature. And the results show that the algorithm can also classifies the extracted object image with improved recognition rate.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.247-250
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• 2011

컴퓨터의 대중화와 각종 디지털 기기의 보급 및 네트워크의 발달로 거의 모든 정보가 디지털화되어 처리 및 저장되고 있는 추세이다. 하지만 이러한 편리한 측면에도 불구하고 개인 신상 정보 유출 및 피싱, 해킹 등으로 인해 아이디/비밀번호와 같은 기존 방식으로는 강화되고 있는 보안에 대한 요구를 충족시킬 수 없는 것이 현실이다. 홍채 인식은 최근들어 출입통제, 정보보안 등의 분야에 많이 활용되고 있다. 홍채 특징 추출 시 크기, 조명, 회전에 무관한 홍채 특징을 추출하는 것이 바람직하다. 홍채크기 및 조명 문제는 전처리를 통해 쉽게 해결할 수 있지만 회전에 무관한 홍채 특징 추출은 여전히 문제가 된다. 본 논문에서는 회전 보정으로 인한 인식률 및 속도 저하를 개선하기 위해 Zernike 모멘트를 통한 홍채특징 추출방법을 제안하였다.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.279-289
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• 2011

The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.131-139
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• 2003

Shape descriptors play an important role in systems for object recognition, retrieval, registration, and analysis. Seven well-known descriptors including MPEG-7 visual descriptors arebriefly reviewed and a new robust pattern recognition descriptor is proposed. Performance comparison among descriptors are presented. Experiments show that the newly proposed descriptor yields better performance results than Fourier, invariant moment, and edge histogram descriptors.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.53-64
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• 2009

This paper presents a performance evaluation of shape descriptors for gait analysis in case of silhouette sequence images. We used moment descriptors(MD), Fourier descriptors(FD) and Zernike descriptors(ZD) as a shape descriptor. To evaluate their performance, we firstly defined the performance index, that is, AI(asymmetry index) and PI(periodic index) based on the periodic property of the gait images. This is why they are represented by periodic parameters due to periodic gait images. This index means that how the shape is represented periodically. According to these indexes, we evaluated the data sets with periodic images, downloaded from internet. The results showed that Zernike descriptors had better performance of AI = 1.09 and PI = 2.21 than others. And in case of FD and ZD, it's efficient to implement the gait analysis with 5~10 parameters.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.153-162
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• 2012

In this paper, we propose a new shape similarity measure for M:N polygon pairs regardless of different object cardinalities in the pairs. The proposed method compares the projections of two shape functions onto Zernike polynomial basis functions, where the shape functions were obtained from each overall region of objects, thus not being affected by the cardinalities of object pairs. Moments with low-order basis functions describe global shape properties and those with high-order basis functions describe local shape properties. Therefore several moments up to a certain order where the original shapes were similarly reconstructed can efficiently describe the shape properties thus be used for shape comparison. The proposed method was applied for the building objects in the New address digital map and a car navigation map of Seoul area. Comparing to an overlapping ratio method, the proposed method's similarity is more robust to object cardinality.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.26-36
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• 2012

Since shape of an object in an image carries important information in contents based image retrieval (CBIR), many shape description methods have been proposed to retrieve images using shape information. Among the existing shape based image retrieval methods, the method which employs invariant Zernike moment desciptor (IZMD) showed better performance compared to other methods which employ traditional Zernike moments descriptor in CBIR. In this paper, we propose a new image retrieval method which applies invariant angular radial transform descriptor (IARTD) to obtain higher performance than the method which employs IZMD in CBIR. IARTD is a rotationally invariant feature which consists of magnitudes and alligned phases of angular radial transform coefficients. To produce rotationally invariant phase coefficients, a phase correction scheme is performed while extracting the IARTD. The distance between two IARTDs is defined by combining the differences of the magnitudes and the aligned phases. Through the experiment using MPEG-7 shape dataset, the average bull's eye performance (BEP) of the proposed method is 0.5806 while the average BEPs of the exsiting methods which employ IZMD and traditional ART are 0.4234 and 0.3574, respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.251-256
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• 2019

In this paper we proposed system and algorithm to recognize hand gestures based on the millimeter wave that is in 65GHz bandwidth. The proposed system is composed of millimeter wave radar board, analog to data conversion and data capture board and notebook to perform gesture recognition algorithms. As feature vectors in proposed algorithm. we used global and local zernike moment descriptor which are robust to distort by rotation of scaling of 2D data. As Experimental result, performance of the proposed algorithm is evaluated and compared with those of algorithms using single global or local zernike descriptor as feature vectors. In analysis of confusion matrix of algorithms, the proposed algorithm shows the better performance in comparison of precision, accuracy and sensitivity, subsequently total performance index of our method is 95.6% comparing with another two mehods in 88.4% and 84%.

• The Magazine of the IEIE
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• v.21 no.10
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• pp.47-54
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• 1994

본 논문에서는 물체들의 이동(translation) 축적(scale) 그리고 회전방향(orientation)에 무관하게 물체를 인식하는 실용적인 패턴 인식 시스템을 소개한다. 이 시스템은 2진영상으로 변환하는데 필요한 임계치(threshold)의 큰 변화에도 덜 민감하다. 특징 벡터(feature vector)로 서는 Zernike 모멘트를 사용하였는데 지금까지 잘 알려진 Hu가 제안한 7개의 모멘트 불변수 (moment invariants)와 비교한다. 또한, 실용적인 기계 시각(machine vision) 시스템에 대해 세 가지 중요한 문제로서 패턴 정규화(pattern nomalization), Zernike 모멘트의 신속한 계산, 그리고 k-NN 규칙을 이용한 분류 등을 논의하였다. 실험에서는 임의의 회전 방향에서 문자들의 크기가 10x10 화소(pixel)에서 512x512 화소까지 변하는 서로 다른 크기를 가진 인쇄된 62개의 문자와 숫자 그리고 기호들을 서로 다른 임계치에서 인식하는 것을 보여준다.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.156-161
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• 1997

Zernike moments have been one of the most commonly used feature vectors for recognizing rotated patterns due to its rotation invariant characteristics. In order to reduce its expensive computational cost, several methods have been proposed to lower the complexity. One of the methods proposed by mukundan and K. R. Ramakrishnan[1], however, is not rotation invariant. In this paper, we propose another method that not only reduces the computational cost but preserves the rotation invariant characteristics. In the experiment, we compare our method with others, in terms of computing time and the accuracy of moment feature at different rotational angle of an object in image.