COMBINING HADAMARD MATRIX, DISCRETE WAVELET TRANSFORM AND DCT FEATURES BASED ON PCA AND KNN FOR IMAGE RETRIEVAL

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FARSI HASSAN; MOHAMADZADEH SAJAD

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Journal Paper

Paper Information

Journal: Majlesi Journal of Electrical Engineering Year:2013 | Volume:7 | Issue:1 (24) Page(s): 9-15

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Information Journal Paper

Title

COMBINING HADAMARD MATRIX, DISCRETE WAVELET TRANSFORM AND DCT FEATURES BASED ON PCA AND KNN FOR IMAGE RETRIEVAL

Author(s)

FARSI HASSAN | MOHAMADZADEH SAJAD | Issue Writer Certificate

Keywords

CONTENT-BASED IMAGE RETRIEVAL (CBIR)

HADAMARD MATRIX AND DISCRETE WAVELET TRANSFORM (HDWT2)

DISCRETE COSINE TRANSFORM (DCT)

Abstract

Image retrieval is one of the most applicable image processing techniques, which have been used extensively. Feature extraction is one of the most important procedures used for interpretation and indexing images in content-based image retrieval (CBIR) systems. Reducing the dimension of feature vector is one of the challenges in CBIR systems. There are many proposed methods to overcome these challenges. However, the rate of image retrieval and speed of retrieval is still an interesting field of research. In this paper, we propose a new method based on the combination of Hadamard matrix, discrete wavelet transform (HDWT2) and discrete cosine transform (DCT) and we used principal component analysis (PCA) to reduce the dimension of feature vector and K-nearest neighbor (KNN) for similarity measurement.The precision at percent recall and ANR are considered as metrics to evaluate and compare different methods.Obtaining results show that the proposed method provides better performance in comparison with other methods.

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APA: Copy

FARSI, HASSAN, & MOHAMADZADEH, SAJAD. (2013). COMBINING HADAMARD MATRIX, DISCRETE WAVELET TRANSFORM AND DCT FEATURES BASED ON PCA AND KNN FOR IMAGE RETRIEVAL. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, 7(1 (24)), 9-15. SID. https://sid.ir/paper/626376/en

Vancouver: Copy

FARSI HASSAN, MOHAMADZADEH SAJAD. COMBINING HADAMARD MATRIX, DISCRETE WAVELET TRANSFORM AND DCT FEATURES BASED ON PCA AND KNN FOR IMAGE RETRIEVAL. MAJLESI JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2013;7(1 (24)):9-15. Available from: https://sid.ir/paper/626376/en

IEEE: Copy

HASSAN FARSI, and SAJAD MOHAMADZADEH, “COMBINING HADAMARD MATRIX, DISCRETE WAVELET TRANSFORM AND DCT FEATURES BASED ON PCA AND KNN FOR IMAGE RETRIEVAL,” MAJLESI JOURNAL OF ELECTRICAL ENGINEERING, vol. 7, no. 1 (24), pp. 9–15, 2013, [Online]. Available: https://sid.ir/paper/626376/en

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