AUTOMATIC IMAGE ANNOTATION USING TWO-LEVEL VISUAL AND SEMANTIC CLUSTERING

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BAHRAMI SAMANE; SANIEE ABADEH MOHAMMAD

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Paper Information

Journal: MACHINE VISION AND IMAGE PROCESSING Year:2015 | Volume:2 | Issue:1 Page(s): 57-74

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Information Journal Paper

Title

AUTOMATIC IMAGE ANNOTATION USING TWO-LEVEL VISUAL AND SEMANTIC CLUSTERING

Author(s)

BAHRAMI SAMANE | SANIEE ABADEH MOHAMMAD | Issue Writer Certificate

Keywords

AUTOMATIC IMAGE ANNOTATION

TWO

LEVEL CLUSTERING

GENETIC ALGORITHM

Abstract

AUTOMATIC IMAGE ANNOTATION refers to automatically assignment of textual labels according to visual content of images. Althoughin the last decade great deal of research has been done in this area, Butbecause of numerous labels and semantic gap between the labels and the low-levelvisualfeatures, the accuracy and efficiency of these systems is reduced. In this study, an annotation method is proposed using TWO-level clustering based on featureswhich are reduced with GENETIC ALGORITHM and as well as semantics. Clustering makes visual similar images and also semantic related images be placed next toeach otherandbe annotated. This leads to fast annotation and also has an acceptable performance for an annotation system. To evaluate the proposed method, TWO well-known datasets, Corel5k and IAPR TC-12 are selected. The results show acceptable performance of the proposed method in comparison with other methods.

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APA: Copy

BAHRAMI, SAMANE, & SANIEE ABADEH, MOHAMMAD. (2015). AUTOMATIC IMAGE ANNOTATION USING TWO-LEVEL VISUAL AND SEMANTIC CLUSTERING. MACHINE VISION AND IMAGE PROCESSING, 2(1 ), 57-74. SID. https://sid.ir/paper/265713/en

Vancouver: Copy

BAHRAMI SAMANE, SANIEE ABADEH MOHAMMAD. AUTOMATIC IMAGE ANNOTATION USING TWO-LEVEL VISUAL AND SEMANTIC CLUSTERING. MACHINE VISION AND IMAGE PROCESSING[Internet]. 2015;2(1 ):57-74. Available from: https://sid.ir/paper/265713/en

IEEE: Copy

SAMANE BAHRAMI, and MOHAMMAD SANIEE ABADEH, “AUTOMATIC IMAGE ANNOTATION USING TWO-LEVEL VISUAL AND SEMANTIC CLUSTERING,” MACHINE VISION AND IMAGE PROCESSING, vol. 2, no. 1 , pp. 57–74, 2015, [Online]. Available: https://sid.ir/paper/265713/en

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