Me | Other works | Students | Journals | Links
    


PhD students

  • Ms. Rashmi Turior (PhD)

    Tortuosity
    • x

  • Ms. Bharima (PhD)

    • x

  • Ms. Sasirassamee (PhD)

    Tortuosity
    • x

  • Ms. Akekaluck Hemtanon (PhD)

    CARBON CREDIIT MANAGEMENT SYSTEM FOR THAILAND
    • Akekaluck Hemtanon and Bunyarit Uyyanonvara, Comparative Survey of appropriate Carbon Credit Registry Systems for Thailand, The 7th International Conference on Computing and Information Technology (IC2IT 2011), pp xxxx Bangkok, May 11 - 12, (May 2011)

  • Ms. Cattleya Duanggate (PhD)

    Blob detection with Scale Space
    • Cattleya Duanggate and Bunyarit Uyyanonvara, A Review of Automatic Drusen Detection and Segmentation from Retinal Images, Proceedings of the International Symposium on Biomedical Engineering (ISBME 2008), pp. 222-225, November 10-11, 2008, Bangkok, Thailand.
    • Jirach Suthammanas, Kanchana Viriyachot, Pantawee Tuntipark, Bunyarit Uyyanonvara, Kamthorn Krairaksa and Cattleya Duanggate, An Automatic Diabetic Retinopathy Telescreening System of Thailand, Proceedings of the International Symposium on Biomedical Engineering (ISBME 2008), pp. 88-92, November 10-11, 2008, Bangkok, Thailand
    • Jirach Suthammanas, Kanchana Viriyachot, Pantawee Tuntipark, Cattleya Duanggate, Bunyarit Uyyanonvara, Sakchai Vongkittirux and Nattapol Wongkamchang, An Implementation of Online Diabetic Retinopathy Screening System, Proceedings of the International Conference on Embedded Systems and Intelligent Technology, February 11-13, 2009, Pattaya, Thailand.
    • Navdeep Saini, Tom Williamson, Sarah Barman, Bunyarit Uyyanonvara Akara Sopharak , Cattleya Duanggate, Automated detection of Age-related Macular Degeneration for screening programmes
      IMAGING IN THE EYE IV, Institute of Physics and British Machine Vision Association, AN IOP-BMVA JOINT EVENT, 28th May 2008, 76 Portland Place, London, W1N 3DH
    • Cattleya Duanggate, Bunyarit Uyyanonvara, and Tawetong Koanantakul, A Review of Image Analysis and Pattern Classification Techniques for Automatic Pap Smear Screening Process, Proceedings of the International Conference on Embedded Systems and Intelligent Technology, pp. 212-217, February 27-29, 2008, Bangkok, Thailand. download

  • Ms. Akara Sopharak (PhD) - Graduated

    AUTOMATIC DETECTION OF DIABETIC RETINOPATHY FROM DIGITAL RETINAL IMAGES
    Thesis Abstract:
    Diabetic retinopathy is a complication of diabetes that is caused by changes in the blood vessels of the retina. The symptoms can blur or distort the patient?s vision and are a main cause of blindness. Exudates are among the preliminary signs of diabetic retinopathy, a major cause of vision loss in diabetic patients. Early detection of exudates could improve patients? chances to avoid blindness. We have proposed and evaluated methods for automatic detection of exudate in non-dilated retinal images using mathematical morphology techniques, fuzzy c-means, and a combination of fuzzy c-means and mathematical morphology. In experiments on comparable data sets, the sensitivity and specificity for these methods were 80.00% and 99.46%, 92.18% and 91.52%, and 86.03% and 99.36%, respectively. While these results are encouraging, they are limited by suboptimal feature selection and pixel classification techniques. A series of experiments on feature selection and exudate classification using naive Bayes and support vector machine (SVM) classifiers are also proposed. We first fit the naive Bayes model to a training set consisting of 15 features extracted from each of 115,867 positive examples of exudate pixels and an equal number of negative examples. We then perform feature selection on the naive Bayes model, repeatedly removing features from the classifier, one by one, until classification performance stops improving. To find the best SVM, we begin with the best feature set from the naive Bayes classifier, and repeatedly add the previously-removed features to the classifier. For each combination of features, we perform a grid search to determine the best combination of hyperparameters ? (tolerance for training errors) and ? (radial basis function width). We compare the best naive Bayes and SVM classifiers to a baseline nearest neighbor (NN) classifier using the best feature sets from both classifiers. We find that the naive Bayes and SVM classifiers perform better than the NN classifier. The overall best sensitivity, specificity, precision, and accuracy are 92.28%, 98.52%, 53.05%, and 98.41%, respectively.
    • Akara Sopharak, Bunyarit Uyyanonvara and Sarah Barman Automatic Microaneurysm Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Mathematical Morphology Methods, IAENG International Journal of Computer Science, 38:3, pp295-301, August 2011 [Online Full Text]
    • Akara Sopharak, Metthew Dailey, Bunyarit Uyyanonvara, Sarah Barman, Tom Williamson, KT New, Y A Moe, Machine Learning Approach to Automatic Exudate Detection in Retinal Images from Diabetic Patients, Journal of Modern Optics Volume 57, Issue 2 January 2010 , pages 124 - 135, doi:10.1080/09500340903118517 (IF: 1.475) download from iFirst (Jan 2010)
    • Akara Sopharak, Bunyarit Uyyanonvara, Sarah Barman, Tom Williamson Comparative Analysis of Automatic Exudate Detection between Machine Learning and Traditional Approaches, IEICE Information System Vol.E92-D, No.11, pp.2264-2271, Nov. 2009 (IF: 0.144) (Nov 2009) download
    • Akara Sopharak, Bunyarit Uyyanonvara, and Sarah Barman Automatic exudate detection from non-dilated diabetic retinopathy retinal images using fuzzy C-means clustering, Sensors, Vol. 9, No. 3, March 2009, pp. 2148-2161; doi:10.3390/s90302148 (IF: 1.573) (March 2009) download
    • Akara Sopharak, Bunyarit Uyyanonvara, Sarah Barman Automatic Exudate Detection for Diabetic Retinopathy Screening, Science Asia Journal Vol. 35 No. 1 pp.80-88 (March, 2009) download
    • Akara Sopharak, Bunyarit Uyyanonvara, Sarah Barman, Thomas H Williamson, Automatic Detection of Diabetic Retinopathy Exudates from Non-Dilated Retinal Images Using Mathematical Morphology Methods, Computerized Medical Imaging and Graphics Volume 32 , Issue 8 , Pages 720 - 727 download (IF: 0.848)(Dec 2008)
    • Akara Sopharak, Khine Thet Nwe, Yin Aye Moe, Matthew N. Dailey, Bunyarit Uyyanonvara ,Sarah Barman, Automatic Exudate Detection with a Support Vector Machine Classifier IMAGING IN THE EYE IV, Institute of Physics and British Machine Vision Association, AN IOP-BMVA JOINT EVENT, 28th May 2008, 76 Portland Place, London, W1N 3DH
    • Akara Sopharak, Khine Thet Nwe, Yin Aye Moe, Matthew N. Dailey and Bunyarit Uyyanonvara, Automatic Exudates Detection with a Naive Bayes Classifier, Proceedings of the International Conference on Embedded Systems and Intelligent Technology, pp. 139-142 ,February 27-29,2008; Bangkok Thailand. download
    • Akara Sopharak and Bunyarit Uyyanonvara, Automatic Exudates Detection from Non-dilated Diabetic Retinopathy Retinal Image Using Fuzzy C-Means Clustering, Proceedings of the Third WACBE World Congress on Bioengineering 2007 (WACBE 2007), July 9-11,2007; Bangkok Thailand. download
    • Akara Sopharak and Bunyarit Uyyanonvara, Automatic Exudates Detection from Diabetic Retinopathy Retinal Image Using Fuzzy C-Means and Morphological Methods, 3rd IASTED International Conference on Advances in Computer Science and Technology (ACST 2007) , pp. 359-364; April 2-4,2007; Phuket Thailand. (2007) download
    • Akara Sopharak and Bunyarit Uyyanonvara, Automatic Exudates Detection on Thai Diabetic Retinopathy Patients' Retinal Images, Proceedings of the 2006 ECTI International Conference, pp.709-712; May (2006) download
    • อัครา โศภารักษ์ และ ผศ.ดร. บุญญฤทธิ ์ อุยยานนวาระ, ระบบการตรวจหาไขมันในชั้นประสาทตา แบบอัตโนมัติจากภาพถ่ายจอประสาทตาของผู้ป่วยโรคเบาหวานขึ้นจอประสาทตาแบบไม่ขยายม่านตา, Proceedings of the 2007 National Science and Technology Development Agency:NSTDA Annaul Conference (NAC2007), March 27-29,2007; NECTEC, Thailand.

  • Ms. Lassada Sukkaew (PhD)

    Image Analysis for automatic dectection of retinopathy of prematurity.
    Thesis Abstract:
    Retinopathy of Prematurity (ROP) is a common retinal neovascular disorder of premature infants. Early detection of the symptoms reduces the risk of permanent blindness. There are many situations where automatic calculation of the vessel tortuosity is crucially important. Retinopathy of Prematurity (ROP), for example, is an infant disease characterized by increased dilation and tortuosity of the eyes blood vessels. Automatic blood vessel tortuosity evaluation is very useful to facilitate ophthalmologist in ROP screening or even prevent childhood blindness. To make these measurements it is necessary to detect the retinal vasculature. However, it is difficult to analyse retinal images of premature infants where image capture can be problematic and low lighting situations result. We propose result of a comparison of edge detection techniques for automatic classification of retinal blood vessels in infant images. The accuracy of methods are examined by comparing the results with hand-drawn ground-truth images. The finding indicats that the sensitivity and specificity of highest results in the first group of operators is Canny operator are 50.08% and 64.77%. Laplacian of Gaussian show best result of 64.81% and 64.23% for a set of 20 images. And we also present a set of methods for detection of the skeletonized structure of premature infant’s low-contrast retinal blood vessel network. With a series of steps statistically optimized for this problem, namely statistically optimized LOG edge detection filter, Otsu thresholding, Medial axis transform skeletonization, pruning, and edge thinning, we produced an output with a high specificity of 0.9879 and sensitivity of 0.8935. In addition we proposed a method to automatically classify an image into two classes, namely tortuous and non-tortuous.The process imitates expert ophthalmologists’ screening method by looking for clearly tortuous vessel segments. Firstly, the skeleton of retinal blood vessel was extracted from the original infant retinal image using a series of morphological operators. Because calculations of the tortuosity are always based on a certain partition of the curve which is not unique and may depend on the human perception, we proposed the partitioning of blood vessel recursively using maximum allowable interpolation error before the tortuosity calculation. The algorithm is based on a linear interpolation procedure with the optimum choice of a maximum allowable interpolation error. Tortuosity was calculated based on the curvature of each of the smaller vessel segments. The retinal images were then classified into two classes using their five most tortuous segments as features for classification. The predictions from the algorithm were then compared to those from expert ophthalmologists. The average accuracy rate received by the system is 98.5 percent.
    • Lassada Sukkaew, Bunyarit Uyyanonvara, Stanislav S. Makhanov, Sarah Barman, Pannet Pangputhipong, Automatic Tortuosity-Based Retinopathy of Prematurity Screening System, accepted by IEICE TRANSACTIONS on Information and Systems (as of August 2008)
    • Lassada Sukkaew, Bunyarit Uyyanonvara, Sarah Barman, Alistair Fielder, Ken Cocker, Automatic extraction of the structure of the retinal blood vessel network of premature infants, Journal of Medical Association of Thailand, Vol.90, No. 9, 2007, pp 1780-1792 download
    • Lassada Sukkaew, Bunyarit Uyyanonvara, A Novel Method for Automatic Measurement of Retinal Vascular Tortuosity in Infant Retinal Images, International workshop on Advance Image Technology (IWAIT2007), January 8-9, Bangkok, Thailand. pp.100 (2007).
    • Lassada Sukkaew, Bunyarit Uyyanonvara, Sarah Barman, Comparison of Edge Detection Techniques on Vessel Detection of Infant’s Retinal Image, International Conference on Computer and Industrial Management (ICIM2005) October 29-30, ABAC, Bangkok, Thailand, pp.6.1-6.5 (2005)
    • Lassada Sukkaew, Bunyarit Uyyanonvara, Automatic skeletonized structure detection of premature infant’s low-contrast retinal blood vessel network, International Conference on Intelligent Technologies (InTech2005), October 14-16, Phuket, Thailand, pp. 3882-3892. (2005).
    • Lassada Sukkaew, Bunyarit Uyyanonvara, Sarah A Barman, Jaruwat Jareanjit, Automated Vessels Detection on Infant Retinal Images, International Conference on Control, Automation and Systems (ICCAS2004), August 25-27, Bangkok, Thailand, pp. 321-325 download
    • Lassada Sukkaew, Bunyarit Uyyanonvara, Sarah Barman, Ken Cocker, Alistair Fielder, Automatic Extraction of The Structure of The Retinal Blood Vessel Network of Premature Infants, Abstract presentaion at Imaging in the eye III Technologies and Clinical Applications conference, Institute of Physics Optical Group, London, UK, http://www.iop.org/IOP/Groups/OP/



Master Students

  • Mr. Pornthep (MSc)

    searching
    1. x

  • Mr. Nuttapong Chaiyawatana (MSc)

    ROBUST OBJECT DETECTION ON VIDEO SURVEILLANCE
    1. Nuttapong Chaiyawatana, Bunyarit Uyyanonvara, Toshiaki Kondo, Premnath Dubey and Yoshinori Hatori, Robust Object Detection on Video Surveillance, Proceeding of the 8th International Joint Conference on Computer Science and Software Engineering (JCSSE), pp. 149 - 153, May 11-13, 2011, Nakorn Pathom, Thailand (May 2011)

  • Mr. Taw (MSc)

    searching
    • x

  • Mr. Krit Intajak (MSc)

    APPLICATIONS OF KNN CLASSIFICATIONS
    • Krit Inthajak, Cattleya Duanggate, Bunyarit Uyyanonvara, Stanislav S. Makhanov and Sarah Barman, Medical Image Blob Detection with Feature Stability and KNN Classification, Proceeding of the 8th International Joint Conference on Computer Science and Software Engineering (JCSSE), pp. 128 - 131, May 11-13, 2011, Nakorn Pathom, Thailand (May 2011)
    • Krit Inthajak, Cattleya Duanggate, Bunyarit Uyyanonvara, Stanislav S. Makhanov, Sarah Barman, Tom Williamson, Variable Size Blob Detection with Feature Stability, Proceedings of the 3rd Biomedical Engineering International Conference on Medical Imaging, Image and Signal Processing, pp. 133 - 137, August 27-28, 2010; Kyoto University, Kyoto, Japan (August 2010)
    • Cattleya Duanggate, Krit Inthajak, Bunyarit Uyyanonvara, Stanislav S. Makhanov, Sarah Barman and Tom Williamson, AUTOMATIC OPTIC DISC DETECTION FOR ROP IMAGES USING SCALE-SPACE THEORY, Proceedings of International Conference on Embedded Systems and Intelligent Technology (ICESIT2010), pp.64, 5-7 Feb 2010, Chiang Mai, Thailand.
    • Krit Inthajak, Nuttapong Chaiyawatana, Chalatip Charuchaimontri, Bunyarit Uyyanonvara, Sissades Tongsima and Sastra Chaotheing, BITE-ME (BIOLOGICAL INTERPREATATION TOOL FOR MALARIA MICROARRAY DATA), Proceedings of the International Symposium on Biomedical Engineering (ISBME 2008), pp. 299-303, November 10-11, 2008, Bangkok, Thailand.

  • Mr. Suthit Rattathanapad (MSc)

    Vessel Segmentation in Retinal Images using Graph-Theoretical Vessel Tracking
    • Suthit Rattathanapad, Bunyarit Uyyanonvara, Pradit Mittrapiyanuruk, Pakorn Kaewtrakulpong, Vessel Segmentation in Retinal Images using Graph-Theoretical Vessel Tracking, 12th IAPR Conference on Machine Vision Applications (MVA2011), pp 548 - 551, Nara, Japan, 13-15 (June 2011) download
      • <

  • Mr. Danu Onkaew (MSc)

    AUTOMATIC RETINAL VESSEL TORTUOSITY MEASUREMENT USING CURVATURE OF IMPROVED CHAIN CODE
    • Danu Onkaew, Rashmi Turior, Bunyarit Uyyanonvara, Nishihara Akinori, Chanjira Sinthanayothin, Automatic Retinal Vessel Tortuosity Measurement using Curvature of Improved Chain Code, International Conference on Electrical, Control and Computer Engineering (InECCE 2011), pp 183-186, 21-22 June 2011 Pahang, Malaysia (June 2011)
    • Danu Onkaew, Rashmi Turior, Bunyarit Uyyanonvara, Toshiaki Kondo, Nishihara Akinori, Chanjira Sinthanayothin, Automatic Extraction of retinal vessels based on Gradient Orientation Analysis, Proceeding of the 8th International Joint Conference on Computer Science and Software Engineering (JCSSE), pp. 102-107, May 11-13, 2011, Nakorn Pathom, Thailand (May 2011)
    • Rashmi Turior, Danu Onkaew, Toshiaki Kondo, Bunyarit Uyyanonvara, A novel approach for quantification of retinal vessel tortuosity based on principal component analysis, Proceeding of 8th Electrical Engineering/Electronics, Computer, Telecommunication & Information Technology Association Conference 2011 (ECTICON 2011),pp1023-1026, May 17-19, 2011, Khon Kaen, Thailand ( May 2011)
    • Onkaew D, Turior R, Uyyanonvara B, Akinori N and Sinthanayothin C., Automatic Vessel Extraction with combined Bottom-hat and Matched-filter, International Conference on Information and Communication Technology for Embedded Systems (ICICTES2011), Pattaya, pp. 101 - 105, January 27-29, 2011, Pattaya, Thailand 2011

  • Mr. Uttapong Ruangrit (Graduated) (MSc)

    MUTation ANnotation Tool
    • Uttapong Ruangrit, Metawee Srikummool, Anunchai Assawamakin, Chumpol Ngamphiw, Suparat Chuechote, Vilasinee Thaiprasarnsup, Gallissara Agavatpanitch, Ekawat Pasomsab, Pa-thai Yenchitsomanus, Surakameth Mahasirimongkol, Wasun Chantratita, Prasit Palittapongarnpim, Bunyarit Uyyanonvara, Chanin Limwongse, and Sissades Tongsima, Thailand Mutation and Variation Database (ThaiMUT), HUMAN MUTATION #1011, 29:E68-E75, 2008 (Online) download
    • Uttapong Ruangrit, Anunchai Assawamakin, Chumpol Ngamphiw, Bunyarit Uyyanonvara, Sissades Tongsima. MUTation ANnotation Tool (MUTANT). Asian Young Researchers Conference on Computational and Omics Biology 2010, March 10-12, 2010.

  • Mr. Thanakorn Suma (MSc)

    METAL ARTIFACT REDUCTION FOR CONE BEAM CT
    • Thanakorn Suma, Suthee Phoojaruenchanachai and Bunyarit Uyyanonvara Comparison of General Interpolation Methods in Projection Modification for Metal Artifacts Reduction in CT, Proceedings of JCSSE 2008 (May 8-9 2008), Vol.1 pp 370-373 download
    • Thanakorn Suma, Bunyarit Uyyanonvara and Suthee Phoojaruenchanachai, Metal Artifact Reduction for Cone Beam CT using Linear Triangular Interpolation, Proceedings of International Conference on Embedded Systems and Intelligent Technology (ICESIT2010), pp 88, 5-7 Feb 2010, Chiang Mai, Thailand.

  • Ms. Viranee Thongnuch (MSc) (Graduated)

    Optic Disk Detection in ROP
    • Viranee Thongnuch and Bunyarit Uyyanonvara, AUTOMATIC OPTIC DISK DETECTION FROM LOW CONTRAST RETINAL IMAGES OF ROP INFANT USING MATHEMATICAL MORPHOLOGY, ICEAST 2007, 21-23 November 2007, Bangkok, Thailand download
    • Viranee Thongnuch and Bunyarit Uyyanonvara, Automatic Detection of Optic Disc from Fundus Images of ROP Infant Using 2D Circular Hough Transform, ISBME2006, November 8-10,2006, Bangkok, pp.328-330 (2006) download
    • Viranee Thongnuch and Bunyarit Uyyanonvara, Automatic Optic Disk Detection from Low Contrast Retinal Images of ROP Infant Using GVF Snake, Suranaree Journal of Science and Technology, Suranaree J. Sci. Technol. 14(3):223-226, 2007 download
    • วิราณี ทองนุช และ ผศ.ดร. บุญญฤทธิ์ อุยยานนวาระ, การใช้เทคนิค GVF SNAKE ในการหาออฟติคดิสก์อย่างอัตโนมัติโดยใช้ภาพเรตินาของเด็กทารกที่เป็น ROPโดยมีความชัดเจนภายในภาพต่ำ, Proceedings of the 2007 National Science and Technology Development Agency:NSTDA Annaul Conference (NAC2007), March 27-29,2007; NECTEC, Thailand.
    • Viranee Thongnuch and Bunyarit Uyyanonvara, AUTOMATIC OPTIC DISK DETECTION FROM LOW CONTRAST RETINAL IMAGES OF ROP INFANT USING MATHEMATICAL MORPHOLOGY, Songklanakarin Journal of Science and Technology - submitted

  • Mr. Nyan Bo Bo (MSc) (Graduated)

    ROBUST HAND TRACKING IN LOW-RESOLUTION VIDEO SEQUENCES
    Thesis Abstract:
    Automatic detection and tracking of human hands in video imagery has many applications. While some success has been achieved in human-computer interaction applications, hand tracking would also be extremely useful in security systems, where it could help the system to understand and predict human actions, intentions, and goals. We have designed and implemented a prototype hand tracking system, which is able to track the hands of moving humans in low resolution video sequences. Our system uses grayscale appearance and skin color information to classify image subwindows as either containing or not containing a human hand. The prototype’s performance is quite promising, detecting nearly all visible hands in a test sequence with a relatively low error rate. In future work we plan to improve the prototype and explore methods for interpreting human gestures in surveillance video.
    • Nyan Bo Bo, Matthew N. Dailey and Bunyarit Uyyanonvara, Robust Hand Tracking in Low-Resolution Video Sequences, , 3rd IASTED International Conference on Advances in Computer Science and Technology (ACST 2007) , pp. 359-364; April 2-4,2007; Phuket Thailand. (2007) download

  • Ms. Y. Sirisathitkula (MSc) (Graduated)

    Color Image Quantization using Adjacent Colors’ Line Segments
    Thesis Abstract:
    This thesis describes a simple but effective hierarchically divisive colormap design technique for color image quantization. By sorting colors based on their components along the principal axis, the one with the highest variance of color distribution, the Euclidean distances between any adjacent colors’ along the axis are used to find the cutting plane that is perpendicular to the axis and divides a color cell into two subcells with approximately equal quantization errors with respect to their centroids. As a result, the total quantization error on both cells is minimal. The experimental results reveal that the proposed algorithm is effective and yields a better execution time when compared with others. Moreover the proposed method performs well on both pictures with 15-bit and 24-bit colors regardless of a number of colors in the colormap.
    • Y. Sirisathitkula, S. Auwatanamongkola and Bunyarit Uyyanonvara, Color Image Quantization using Adjacent Colors’ Line Segments. Journal of Pattern Recognition Letters, Vol 25/9 pp 1025-1043. (2004) - download
    • Y. Sirisathitkula, S. Auwatanamongkola and Bunyarit Uyyanonvara, Fast Color Image Quantization using Squared Euclidean Distance of adjacent color points along the 1D Highest Color Variance Axis, Proceedings of the 17th International Conference on Pattern Recognition 2004 (ICPR 2004), August 23-26, Cambridge, UK, volume1, pp.656-659. (2004) download

  • Mr. Kaittisin Kanjanawanishkul (MSc)

    Fast Adaptive Algorithm for Time-Critical Color Quantization Application
    Thesis Abstract:
    In this paper, we propose a new adaptive approach of color quantization. It can significantly reduce the time consumption during the process compared with available methods but still maintains a good quality (greater than 30 dB of PSNR). It is implemented as a part of the media stream compression algorithms for a True Color Signboard System. We adapt and create some techniques to speed up the process. We start with a sampling technique on an RGB color space before constructing the 3D histogram of color distribution, and then we use the dynamic programming based on Wus algorithm to construct the cumulative moment distribution. Then, we put the cutting plane through the centroid of that box. This plane is perpendicular to the axis, on which the sum of the squared Euclidean distances between the centroid of both of sub-boxes and the centroid of the box is the greatest. The sub-box, which contains the greatest value representing variance, is repeatedly sub-divided into the smaller sub-boxes until reaching the desired number of the representative colors. From our whole process, we gain approximately up to 50% less time consumption than Wus quantizer [ACM Trans. Graph. 11 (1992) 348] and it is significantly faster than existing algorithms as shown in the result.
    • Kiattisin Kanjanawanishkul and Bunyarit Uyyanonvara, Novel fast color reduction algorithm for time-constrained applications, Journal of Visual Communication and Image Representation, Volume 16, Issue 3, June 2005, pp. 311-332 (2005) download
    • K. Kanjanawanishkul and Bunyarit Uyyanonvara, Fast Color Quantization Using Image Sub-sampling Technique, InTech03, Chiangmai, Thailand, Inter Conf. Proceeding. pp.376-383 (2003)
    • K. Kanjanawanishkul and Bunyarit Uyyanonvara, Fast Adaptive Algorithm for Time-Critical Color Quantization Application, DICTA2003, Proc. VIIth Digital Image Computing: pp.781-790.,10-12 Dec. 2003, Sydney, Australia. (2003) download



Senior Projects
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011
  • Mr. A, Ms. B - project name - 2011



Thesis External Examiner
  • Muscular Contraction Classifier using Principle Component Analysis (Direk Suersinak) Faculty of Engineering, KMITL (M.Eng.) 2007
  • Fast Color Image Quantization using Squared Euclidean Distance of adjacent color points along the 1D Highest Color Variance Axis(Y. Sirisathitkul) NIDA (MSc.) 2004

Google   
  Template & PHP Engine powered by Bunyarit Uyyanonvara - copyright © 2002 all rights reserved.