CONCEPT DETECTION IN IMAGES USING SVD FEATURES AND MULTI-GRANULARITY PARTITIONING AND CLASSIFICATION

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FARAJZADEH KAMRAN; zarezadeh Esmail; MANSOURI JAFAR

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Journal Paper

Paper Information

Journal: Journal of Information Systems and Telecommunication Year:2017 | Volume:5 | Issue:3 Page(s): 172-182

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Title

CONCEPT DETECTION IN IMAGES USING SVD FEATURES AND MULTI-GRANULARITY PARTITIONING AND CLASSIFICATION

Author(s)

FARAJZADEH KAMRAN | zarezadeh Esmail | MANSOURI JAFAR | Issue Writer Certificate

Keywords

HIGH-DIMENSIONAL DATA

MULTI-GRANULARITY PARTITIONING AND CLASSIFICATION

MULTIPLICATIVE DISTANCE

SEMANTIC CONCEPT DETECTION

STATIC VISUAL FEATURES

SVD

Abstract

New visual and static features, namely, right singular feature vector, left singular feature vector and singular value feature vector are proposed for the SEMANTIC CONCEPT DETECTION in images. These features are derived by applying singular value decomposition (SVD) "directly" to the "raw" images. In SVD features edge, color and texture information is integrated simultaneously and is sorted based on their importance for the concept detection. Feature extraction is performed in a multi-granularity partitioning manner. In contrast to the existing systems, classification is carried out for each grid partition of each granularity separately. This separates the effect of classifications on partitions with and without the target concept on each other. Since SVD features have high dimensionality, classification is carried out with K-nearest neighbor (K-NN) algorithm that utilizes a new and "stable" distance function, namely, MULTIPLICATIVE DISTANCE. Experimental results on PASCAL VOC and TRECVID datasets show the effectiveness of the proposed SVD features and MULTI-GRANULARITY PARTITIONING AND CLASSIFICATION method.

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APA: Copy

FARAJZADEH, KAMRAN, zarezadeh, Esmail, & MANSOURI, JAFAR. (2017). CONCEPT DETECTION IN IMAGES USING SVD FEATURES AND MULTI-GRANULARITY PARTITIONING AND CLASSIFICATION. JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST), 5(3), 172-182. SID. https://sid.ir/paper/332743/en

Vancouver: Copy

FARAJZADEH KAMRAN, zarezadeh Esmail, MANSOURI JAFAR. CONCEPT DETECTION IN IMAGES USING SVD FEATURES AND MULTI-GRANULARITY PARTITIONING AND CLASSIFICATION. JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST)[Internet]. 2017;5(3):172-182. Available from: https://sid.ir/paper/332743/en

IEEE: Copy

KAMRAN FARAJZADEH, Esmail zarezadeh, and JAFAR MANSOURI, “CONCEPT DETECTION IN IMAGES USING SVD FEATURES AND MULTI-GRANULARITY PARTITIONING AND CLASSIFICATION,” JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST), vol. 5, no. 3, pp. 172–182, 2017, [Online]. Available: https://sid.ir/paper/332743/en

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