Foot Recognition using LBP-kNN for Knee Rehabilitation
| Autor: | Jermphiphut Jaruenpunyasak, Pakpoom Hoyingcharoen, Mongkol Saejia, Rakkrit Duangsoithong |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Foot (prosody)
0209 industrial biotechnology Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition 02 engineering and technology Knn classifier Svm classifier ComputingMethodologies_PATTERNRECOGNITION 020901 industrial engineering & automation Knee rehabilitation 0202 electrical engineering electronic engineering information engineering Recognition system 020201 artificial intelligence & image processing Gait pattern Artificial intelligence business |
| Zdroj: | 2018 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). |
| DOI: | 10.1109/ecticon.2018.8619876 |
| Popis: | The foot recognition can be used in many applications such as gait pattern and knee monitoring exercises; nonetheless, the environment condition and a variety of foot are the main problems of the recognition. In general, the foot recognition system is designed in a closed room or a static background to recognize with bare foot in the same view but it is inconvenience for knee monitoring exercises for a patient. This paper presents a method for the foot recognition using LBP features with kNN classifier. The results are evaluated by accuracy and complexity. These results are also compared with HOG algorithm and SVM classifier. According to the results,the LBP-KNN techniques provides higher accuracy but higher complexity than other methods to recognize the foot from human image. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|