In this paper, we adopt a new local binarization method as an important stage in text detection problem in scene image. Then we compare this new binarization method with our previous proposed binarization method which depends on using the Naïve Bayes classifier to classify the image pixels into foreground and background sets. After this, we apply the connected components analysis to get the morphological properties of each connected component (CC). These properties make used in the next stage to distinguish between text region and non-text region. Our proposed binarization method outperforms the well-known adaptive threshold method with respect to the Precession metric. That is in this paper, we target to satisfy two benefits; the first benefit is to enhance our previous model which be used to extract the characters’ regions in scene images. This enhancement will be shown from the maximizing the Recall metric and this enhancement is fulfilled by considering a new binarization method, Bradley method. The second benefit to show the difference between our previous binarization method and the new one, Bradley method with respect to Recall and Precession metrics.
(2018). A SIMPLE NOVEL EFFECTIVE APPROACH TO DETECT CHARACTERS IN SCENE IMAGES. Assiut University Journal of Multidisciplinary Scientific Research, 47(2), 58-73. doi: 10.21608/aunj.2018.221216
MLA
. "A SIMPLE NOVEL EFFECTIVE APPROACH TO DETECT CHARACTERS IN SCENE IMAGES", Assiut University Journal of Multidisciplinary Scientific Research, 47, 2, 2018, 58-73. doi: 10.21608/aunj.2018.221216
HARVARD
(2018). 'A SIMPLE NOVEL EFFECTIVE APPROACH TO DETECT CHARACTERS IN SCENE IMAGES', Assiut University Journal of Multidisciplinary Scientific Research, 47(2), pp. 58-73. doi: 10.21608/aunj.2018.221216
VANCOUVER
A SIMPLE NOVEL EFFECTIVE APPROACH TO DETECT CHARACTERS IN SCENE IMAGES. Assiut University Journal of Multidisciplinary Scientific Research, 2018; 47(2): 58-73. doi: 10.21608/aunj.2018.221216
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