A Color-Based Text Detection Scheme for Nature Scene Images

• Main Authors: Hong-sih Lin, 林宏賜
• Other Authors: Hsing-Lung Chen
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/67810782826064067934

碩士 === 國立臺灣科技大學 === 電子工程系 === 102 === Recently, researches on text detection have attracted extensive attention. There are two factors affecting text detection: non-uniform illumination and complex background. Many researches have proposed the methods to improve the precision of text detection. Due to the effects of non-uniform illumination and complex background, they can’t obtain a significant improvement. This thesis proposes a color-based text detection strategy which eliminates the effects of non-uniform illumination and complex background, resulting in improving the precision of text detection. The region which can’t be perceived as any color easily is defined as quasi-gray region; otherwise, it is defined as color region. For quasi-gray regions, the difference of hue between pixels in the region are large. While the difference of hue between pixels in the same color region are extremely small. For the convenience of implementation, the color regions are divided into six categories: R+, R-, G+, G-, B+, and B-. After color regions are formed, the edges between different colors can be extracted from six categories separately. However, for quasi-gray texts in the color region, many false edges may be extracted due to divergent hues in quasi-gray texts. This thesis proposes a new metric, called color-intensity. The color-intensity in the quasi-gray region is small, while the color-intensity in the color region is relatively high. Employing the color-intensity, the quasi-gray texts in the color region can be easily detected. Experiment results show that our proposed method can obtain a more accurate outline of texts, resulting in improving the precision of text detection.