Face image retrieval using wavelet transform and dimensionality reduction methods

Content-based face image retrieval is an active research area of wide applications. Face image retrieval techniques can be used in applications such as crime prevention, security check, etc. This paper focuses on content-based facial image retrieval based on combination of wavelet transform with dimensionality reduction methods. Reduced feature sets are extracted through combination of Discrete Wavelet Transform (DWT) and dimensionality reduction techniques such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The databases used for this retrieval process are INDIAN and CalTech. Performance measures precision and recall are used to evaluate the performance of the retrieval process. The results show that DWT-PCA outperforms DWT-LDA, which gives an average precision of 75% for INDIAN and 53% for CalTech.