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The traditional method of retrieval of images using text based technique has various limitations, one of which is the huge amount of labor work required to annotate the image manually. The annotation process takes a lot of time. Another limitation is the interpretation of same image by different people differently which may lead to inaccuracy of results. To overcome these limitations we use visual concept detection. This paper proposes an efficient method of concept detection using various features such as color and texture. For extraction of color feature we use color histogram and color auto correlogram. Features related to texture are being extracted using wavelet transform and Gabor wavelet filter. For classification of images, Support vector machine (SVM) is used depending upon their categories and classes. Wang’s database is used for implementation. By using precision, recall and accuracy as evaluation parameters the performance of proposed system is evaluated


Visual concept detection, color features, texture features, Auto Correlogram, SVM.

Article Details

How to Cite
Vibha Merchant and Sanjay Patil, “VISUAL CONCEPT DETECTION IN IMAGES”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 5, p. 13, Jun. 2020.


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