Diagnosis of Burn Images using Template Matching, k-Nearest Neighbor and Artificial Neural Network

International Journal of Image Processing

Sivakumar¹  U. C. Niranjan¹  Kamal Kumar¹  Malini Suvarna¹ 

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关键词: ANN;    TM;    kNN.;   

DOI  :  

来源: Computer Science Journals

【 摘 要 】

The aim of this research is to develop an automated method of determining the severity of skin burnwounds. Towards achieving this aim, a database of skin burn images has been created by collectingimages from hospitals, doctors and the Internet. The initial pre-processing involves contrastenhancement in lab color space by taking luminance component. Various pattern analysis or patternclassifier techniques viz. Template Matching (TM), k Nearest Neighbor Classifier (kNN) and ArtificialNeural Network (ANN) have been applied on skin burn images and a performance comparison of thethree techniques has been made. The help of dermatologists and plastic surgeons has been taken tolabel the images with skin burn grades and are used to train the classifiers. The algorithms areoptimized on pre-labeled images, by fine-tuning the classifier parameters. During the course ofresearch, of the three classifier methods used for classification of burn images it has been observedthat the ANN technique reflected the best results. This has been inferred based on the comparativestudies of the three methods. In the ANN method the classification of the image of burns has beenfound to be the nearest to the actual burns. The efficiency of the analysis and classification of theANN technique has been of the order of 95% for Grade-1 burns, 97.5% for Grade-2 burns and 95%for Grade-3 burns. As compared to 55%, 72.5% and 70% for Grade1, Grade2, and Grade 3 burnsrespectively for the TM Method and 67.5%, 82.5% and 75% for kNN method. It is therefore felt thatthe ANN technique could be applied to analyze and classify the severity of burns. This burn analysistechnique could be safely used in remote location where specialists’ services are not readily available.The local doctors could use the analyzer and classify the grade of the burn with a good degree ofaccuracy and certainty. They could start preliminary treatment accordingly, prior to specialists’services. This would definitely go a long way in mitigating the pain and sufferings of the patients.

【 授权许可】

Unknown