• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.29-35
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• 2010

In this paper, we introduce a novel entropy coding method to improve the JPEG image compression standard. JPEG is one of the most widely used image compression methods due to its high visual quality for the compression ratio, and especially because of its high efficiency. Based on the observation that the blocks of data fed to the entropy coder usually contain consecutive sequences of numbers with small magnitudes including 0, 1, and -1, we separate those sequences from the data and encode them using a method dedicated to those values. We further improve the compression ratio based on the fact that this separation makes the lengths of blocks much shorter. In our experiment, we show that the proposed method can outperform the JPEG standard preserving its visual characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.972-980
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• 2022

The butterfly species recognition technology based on machine learning using images has the effect of reducing a lot of time and cost of those involved in the related field to understand the diversity, number, and habitat distribution of butterfly species. In order to improve the accuracy and time efficiency of butterfly species classification, various features used as the inputs of machine learning models have been studied. Among them, branch length similarity(BLS) entropy or color intensity entropy methods using the concept of entropy showed higher accuracy and shorter learning time than other features such as Fourier transform or wavelet. This paper proposes a feature extraction algorithm using RGB color intensity entropy for butterfly color images. In addition, we develop butterfly recognition systems that combines the proposed feature extraction method with representative ensemble models and evaluate their performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.298-301
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• 1992

A digital image processing approach has been adopted to measure the flank wear area, which is very difficult to measure using conventional techniques. Automatic thresholding of the gray-level values of an image is very useful in automated analysis of image. 1-D entropy thresholding technique is used for image processing and analysis of the flank wear area. This strategy provides more information about drill wear conditions and should therefore have a higher reliability than previous methods. This study calulated quantitatively the flank were area of drill by computer program.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.1
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• pp.39-47
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• 2001

A blocked zerotree coding algorithm for compression of subband image is proposed. Significance of blocks with respect to a certain threshold are coded with a set of transition rules for the significance of blocks. Significant blocks are quantized by vector quantization. The basic idea for this coding approach are: 1) Subband images are coded by blocks, 2) Important blocks based on the significance of blocks are coded and quantized, 3) Multiband codebook which is composed of sub-codebooks dedicated for each threshold and subband level is adapted to produce good reproduction vectors for vector quantization. The compression results are similar to Shapiro's zerotree coding even though ours are obtained without entropy coding of bit streams from blocked zerotree encoder. If an entropy coding is applied to the bitstream, PSNR will be improved.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.49-58
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• 1993

Extended reduced difference pyramid (ERDP) is proposed for lossless progressive image transmission, which is based on a new transform called rounded-transform(RT). The RT is a nonlinear and reversible transform of integers into integers utilizing two kinds of the rounding operations such as round up and down. The ERDP can be obtained from an N-poing RT or a series of RTs of both. For the performance evaluation, the entropy of the difference images to be transmitted is used as a lower bound transmission rate. Two examples of the ERDP can be easily shown, which is more effective in the entropy than the ordinary RDP.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.810-812
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• 2014

In this paper, a hagwon-bus boarding danger warning system based on computer vision is proposed to protect children from an accident causing injuries or death. Three zones are defined and different algorithms are applied to detect moving objects. In zone 1, a block-based entropy value is calculated using the absolute difference image generated by the absolute differential estimation between background image and incoming video frame. In zone 2, an effective and robust motion object tracking algorithm is performed based on the particle filter. Experimental results demonstrate the efficient and effectively of the algorithm for moving object inspection in each zone.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.88-96
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• 1994

This paper proposes a new vector quantization scheme which exploits high correlations among indexes in vector quantization. An optimal vector quantizer in the rate-distortion sense can be obtained, if it is designed so that the average distortion can be minimized under the constraint of the conditional entropy of indes, which is usually much smaller than the entropy of index due to the high correlations among indexes of neighboring vectors. The oprimization process is very similar to that in ECVQ(entropy-constrained vector quanization) except that in the proposed scheme the Viterbi algorithm is introduced to find the optimal index sequence. Simulations show that at the same bitrate the proposed method provides higher PSNR by 1.0~3.0 dB than the conventional ECVQ when applied to image coding.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.1-8
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• 2006

This paper proposes an improved FCM(Fuzzy C-means) algorithm using intercluster and entropy-based weight in gray image. The fuzzy clustering methods have been extensively used in the image segmentation since it extracts feature information of the region. Most of fuzzy clustering methods have used the FCM algorithm. But, FCM algorithm is still sensitive to noise, as it does not include spatial information. In addition, it can't correctly classify pixels according to the feature-based distributions of clusters. To solve these problems, we applied a weight and intercluster to the traditional FCM algorithm. A weight is obtained from the entropy information based on the cluster's number of neighboring pixels. And a membership for one pixel is given based on the information considering the feature-based intercluster. Experiments has confirmed that the proposed method was more tolerant to noise and superior to existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2677-2684
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• 2009

In this paper, we study a watermarking method based on the informed coding and embedding by means of trellis code and entropy masking. An image is divided as $8{\times}8$ block with no overlapping and the discrete cosine transform(DCT) is applied to each block. Then the 16 medium-frequency AC terms of each block are extracted. Next it is compared with gaussian random vectors having zero mean and unit variance. As these processing, the embedding vectors with minimum value of linear combination between linear correlation and Watson distance can be obtained by Viterbi algorithm at each stage of trellis coding. For considering the image characteristics, we apply different weight value between the linear correlation and the Watson distance using the entropy masking. To evaluate the performance of proposed method, the average bit error rate of watermark message is calculated from different several images. By the experiments the proposed method is improved in terms of the average bit error rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1194-1208
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• 2010

As visual surveillance systems gain wider usage in a variety of fields, it is important that they are capable of interpreting scenes automatically, also known as "human motion analysis" (HMA). However, existing HMA methods are too domain specific and computationally expensive. This paper proposes a general purpose HMA method that is based on the idea that human beings tend to exhibit erratic motion patterns during abnormal situations. Limb movements are characterized using the statistics of angular and linear displacements. In addition, the method is enhanced via the use of the entropy of the Fourier spectrum to measure the randomness of subject's motions. Various experiments have been conducted and the results indicate that the proposed method has very high classification accuracy in identifying anomalous behavior.