Novel Segmentation Method for Classification of RGB Image at Object Detection Analysis
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Keywords

CBIR, Feature extraction, Image enhancement, Machine vision

How to Cite

Shafei, S. ., & Sedghi, T. . (2013). Novel Segmentation Method for Classification of RGB Image at Object Detection Analysis. Journal of Asian Scientific Research, 3(1), 114–121. Retrieved from https://archive.aessweb.com/index.php/5003/article/view/3453

Abstract

We introduce a new object detection method which has been obtained as main contribution of this paper and a new feature extraction based on wavelet analysis is presented. Image retrieval based on region is one of the most promising and active research directions in recent years. As literature prove that region segmentation will produce better results. Human visual perception is more effective than any machine vision systems for extracting semantic information from image; hitherto no specific system has been suggested with the ability of extracting object individually. In this paper Expectation Maximization is applied on RGB image to classify the objects and then feature extraction method is used for generating new features. The method is compared with some techniques and our proposed method has lots of superiority to previously techniques such as accuracy and good precision.

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