Efficient and accurate document image classification algorithms for low-end copy pipelines

Huang, Wen-Hsiung; Chen, Yung-Yao; Lin, Pei-Yu; Hsu, Che-Hao; Hua, Kai-Lung

doi:10.1186/s13640-016-0135-4

Cited by 3 publications

(1 citation statement)

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“…However, it might be a severe challenge in image document processing pipelines. Assume, for instance, an auto-cropping technique can be used by a scanner for removing the regions beyond a predefined threshold value [19,20]. Auto-cropping might not happen when there is the presence of the chequerboard artefact in the output image since the intensity values are below the predefined threshold.…”

Section: Introductionmentioning

confidence: 99%

Reduction of Artefacts in JPEG-XR Compressed Images

Hua

Trang

Srinivasan

et al. 2019

Sensors

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The JPEG-XR encoding process utilizes two types of transform operations: Photo Overlap Transform (POT) and Photo Core Transform (PCT). Using the Device Porting Kit (DPK) provided by Microsoft, we performed encoding and decoding processes on JPEG XR images. It was discovered that when the quantization parameter is >1-lossy compression conditions, the resulting image displays chequerboard block artefacts, border artefacts and corner artefacts. These artefacts are due to the nonlinearity of transforms used by JPEG-XR. Typically, it is not so visible; however, it can cause problems while copying and scanning applications, as it shows nonlinear transforms when the source and the target of the image have different configurations. Hence, it is important for document image processing pipelines to take such artefacts into account. Additionally, these artefacts are most problematic for high-quality settings and appear more visible at high compression ratios. In this paper, we analyse the cause of the above artefacts. It was found that the main problem lies in the step of POT and quantization. To solve this problem, the use of a “uniform matrix” is proposed. After POT (encoding) and before inverse POT (decoding), an extra step is added to multiply this uniform matrix. Results suggest that it is an easy and effective way to decrease chequerboard, border and corner artefacts, thereby improving the image quality of lossy encoding JPEG XR than the original DPK program with no increased calculation complexity or file size.

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Section: Introductionmentioning

confidence: 99%