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| A New Method for Indoor-outdoor Image Classification Using Color Correlated Temperature
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Full
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Complete Issue PDF(2.53MB) |
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Volume: 6 Issue: 3 |
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Pages: |
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Publication
Date: June 2012 |
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ISSN
(Online): 1985-2304 |
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Pages |
167 - 181 |
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Author(s) |
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Published
Date |
20-06-2012 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Indoor-outdoor Image Classification, Color Segmentation, Color Correlated Temperature |
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| In this paper a new method for indoor-outdoor image classification is presented; where the concept of Color Correlated Temperature is used to extract distinguishing features between the two classes. In this process, using Hue color component, each image is segmented into different color channels and color correlated temperature is calculated for each channel. These values are then incorporated to build the image feature vector. Besides color temperature values, the feature vector also holds information about the color formation of the image. In the classification phase, KNN classifier is used to classify images as indoor or outdoor. Two different datasets are used for test purposes; a collection of images gathered from the internet and a second dataset built by frame extraction from different video sequences from one video capturing device. High classification rate, compared to other state of the art methods shows the ability of the proposed method for indoor-outdoor image classification. |
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| Ali Nadian Ghomsheh : Colleagues
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| Alireza Talebpour : Colleagues
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