New Fast Principal Component Analysis For Real-Time Face Detection

• Autorzy: El-Bakry H. M.
• Języki publikacji: EN

Abstrakty

EN

Principal component analysis (PCA) has various important applications, especially in pattern detection, such as face detection and recognition. In real-time applications, the response time must be as short as possible. In this paper, a new implementation of PCA for fast face detection is presented. Such implementation relies on performing cross-correlation in the frequency domain between the input image and eigenvectors (weights). Furthermore, this approach is developed to reduce the number of computation steps required by fast PCA. The "divide and conquer" principle is applied through image decomposition. Each image is divided into smaller-size sub-images, and then each of them is tested separately using a single fast PCA processor. In contrast to using only fast PCA, the speed-up ratio increases with the size of the input image when using fast PCA and image decomposition. Simulation results demonstrate that the proposed algorithm is faster than conventional PCA. Moreover, experimental results for different images show its good performance. The proposed fast PCA increases the speed of face detection, and at the same time does not affect the performance or detection rate.

Słowa kluczowe

EN

image decomposition; fast PCA; cross-correlation; frequency domain; face detection

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2009
• Tom: Vol. 18, No. 4
• Strony: 405--425
• Opis fizyczny: Bibliogr. 48 poz., il., tab.

Twórcy

autor

El-Bakry H. M.

• Faculty of Computer Science & Information Systems, Mansoura University, Egypt,

Bibliografia

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• [36] Hazem M. El-Bakry, and Nikos Mastorakis "Fast Information Retrieval from Web Pages," Accepted for publication in the Proc. of 7th WSEAS Int. Conf. on Computational Intelligence, Man-Machine Systems and Cybernetics (CIMMACS '08), Cairo, EGYPT, Dec. 29-31.2008.
• [37] Hazem M. El-Bakry and Mohamed Hamada, "New Fast Decision Tree Classifier for Identifying Protein Coding Regions," Lecture Notes in Computer Science, Springer, ISICA 2008, LNCS 5370, pp. 489-500. 2008.
• [38] Hazem M. El-Bakry, and Nikos Mastorakis, "An Effective Method for Detecting Dental Diseases by using Fast Neural Networks," 8th WSEAS International Conference on SIGNAL, SPEECH AND IMAGE PROCESSING (SSIP '08), Santander, Cantabria, Spain, September 23-25, pp. 144-152. 2008.
• [39] Hazem M. El-Bakry, and Nikos Mastorakis, "A New Fast Forecasting Technique using High Speed Neural Networks," 8th WSEAS International Conference on SIGNAL, SPEECH AND IMAGE PROCESSING (SSIP '08), Santander, Cantabria, Spain, September 23-25, pp. 116-138. 2008.
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• [41] Hazem M. El-Bakry, and Nikos Mastorakis, "A New Technique for Detecting Dental Diseases by using High Speed Neuro-Computers," 8th WSEAS International Conference on SIMULATION, MODELLING and OPTIMIZATION (SMO '08), Santander, Cantabria, Malta, September 11-13, pp. 261-279. 2008.
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