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Text Extraction In Natural Scenes Using Region-Based Method, Zhihu Huang, Jinsong Leng
Text Extraction In Natural Scenes Using Region-Based Method, Zhihu Huang, Jinsong Leng
Research outputs 2014 to 2021
Text in images is a very important clue for image indexing and retrieving. Unfortunately, it is a challenging work to accurately and robustly extract text from a complex background image. In this paper, a novel region-based text extraction method is proposed. In doing so, the candidate text regions are detected by 8-connected objects detection algorithm based on the edge image. Then the non-text regions are filtered out using shape, texture and stroke width rules. Finally, the remaining regions are grouped into text lines. Since stroke width is the intrinsic and particular characteristics of the text, the accuracy of the non-text …
An Information-Theoretic Image Quality Measure: Comparison With Statistical Similarity, Asmhan F. Hassan, Dong Cailin, Zahir M. Hussain
An Information-Theoretic Image Quality Measure: Comparison With Statistical Similarity, Asmhan F. Hassan, Dong Cailin, Zahir M. Hussain
Research outputs 2014 to 2021
We present an information-theoretic approach for structural similarity for assessing gray scale image quality. The structural similarity measure SSIM, proposed in 2004, has been successflly used and verfied. SSIM is based on statistical similarity between the two images. However, SSIM can produce confusing results in some cases where it may give a non-trivial amount of similarity for two different images. Also, SSIM cannot perform well (in detecting similarity or dissimilarity) at low peak signal to noise ratio (PSNR). In this study, we present a novel image similarity measure, HSSIM, by using information - theoretic technique based on joint histogram. The …
A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong
A Survey Of Image Processing Techniques For Agriculture, Lalit Saxena, Leisa Armstrong
Research outputs 2014 to 2021
Computer technologies have been shown to improve agricultural productivity in a number of ways. One technique which is emerging as a useful tool is image processing. This paper presents a short survey on using image processing techniques to assist researchers and farmers to improve agricultural practices. Image processing has been used to assist with precision agriculture practices, weed and herbicide technologies, monitoring plant growth and plant nutrition management. This paper highlights the future potential for image processing for different agricultural industry contexts.