EFFICIENT IMAGE COMPRESSION AND DECOMPRESSION ALGORITHMS FOR OCR SYSTEMS

This paper presents an efficient new image compression and decompression methods for document images, intended for usage in the pre-processing stage of an OCR system designed for needs of the “Nikola Tesla Museum” in Belgrade. Proposed image compression methods exploit the Run-Length Encoding (RLE) algorithm and an algorithm based on document character contour extraction, while an iterative scanline fill algorithm is used for image decompression. Image compression and decompression methods are compared with JBIG2 and JPEG2000 image compression standards. Segmentation accuracy results for ground-truth documents are obtained in order to evaluate the proposed methods. Results show that the proposed methods outperform JBIG2 compression regarding the time complexity, providing up to 25 times lower processing time at the expense of worse compression ratio results, as well as JPEG2000 image compression standard, providing up to 4-fold improvement in compression ratio. Finally, time complexity results show that the presented methods are sufficiently fast for a real time character segmentation system

Dynamic Background Segmentation for Remote Reference Image Updating within Motion Detection JPEG2000

International audienceWe present in this paper a new system based on Motion JPEG2000 intended for road surveillance application. The system uses a reference image and consists in 4 processing steps, namely initialization phase where the first reference image is built, reference estimation, motion segmentation (foreground extraction, ROI mask), and JPEG2000 coding. A first order recursive filter is used to build a reference image that corresponds to the background image. The obtained background is sent to the decoder once for all. The reference image at the coder side is estimated according to a Gaussian mixture model. The remote reference image is updated when specific conditions are met. The updating remote reference is triggered according to the states of mobile objects in the scene (no, few or lot of mobiles). The motion detection given by classical background subtraction technique is performed in order to extract a binary mask. The motion mask gives the region of interest of the system. The JPEG2000 image coded with a ROI option is sent towards the decoder. The decoder receives, decodes the image and builds the implicit binary ROI mask. Then, the decoder builds the displayed image using the reference image, the current image and the mask

Low Complexity RDO Model for Locally Subjective Quality Enhancement in LAR Coder

International audienceThis paper introduces a rate distortion optimization (RDO) scheme with subjective quality enhancement applied to a still image codec called Locally Adaptive Resolution (LAR). This scheme depends on the study of the relation between compression efficiency and relative parameters, and has a low complexity. Linear models are proposed first to find suitable parameters for RDO. Next, these models are combined with an image segmentation method to improve the local image quality. This scheme not only keeps an effective control in balance between bitrate and distortion, but also improves the spatial structure of images. Experiments are done both in objective and subjective ways. Results show that after this optimization, LAR has an efficient improvement of subjective image quality of decoded images. This improvement is significantly visible and compared with other compression methods using objective and subjective quality metrics

WG1N5315 - Response to Call for AIC evaluation methodologies and compression technologies for medical images: LAR Codec

This document presents the LAR image codec as a response to Call for AIC evaluation methodologies and compression technologies for medical images.This document describes the IETR response to the specific call for contributions of medical imaging technologies to be considered for AIC. The philosophy behind our coder is not to outperform JPEG2000 in compression; our goal is to propose an open source, royalty free, alternative image coder with integrated services. While keeping the compression performances in the same range as JPEG2000 but with lower complexity, our coder also provides services such as scalability, cryptography, data hiding, lossy to lossless compression, region of interest, free region representation and coding

Low Complexity RDO Model for Locally Subjective Quality Enhancement in LAR Coder

International audienceThis paper introduces a rate distortion optimization (RDO) scheme with subjective quality enhancement applied to a still image codec called Locally Adaptive Resolution (LAR). This scheme depends on the study of the relation between compression efficiency and relative parameters, and has a low complexity. Linear models are proposed first to find suitable parameters for RDO. Next, these models are combined with an image segmentation method to improve the local image quality. This scheme not only keeps an effective control in balance between bitrate and distortion, but also improves the spatial structure of images. Experiments are done both in objective and subjective ways. Results show that after this optimization, LAR has an efficient improvement of subjective image quality of decoded images. This improvement is significantly visible and compared with other compression methods using objective and subjective quality metrics

Screen Content Image Segmentation Using Sparse-Smooth Decomposition

Sparse decomposition has been extensively used for different applications including signal compression and denoising and document analysis. In this paper, sparse decomposition is used for image segmentation. The proposed algorithm separates the background and foreground using a sparse-smooth decomposition technique such that the smooth and sparse components correspond to the background and foreground respectively. This algorithm is tested on several test images from HEVC test sequences and is shown to have superior performance over other methods, such as the hierarchical k-means clustering in DjVu. This segmentation algorithm can also be used for text extraction, video compression and medical image segmentation.Comment: Asilomar Conference on Signals, Systems and Computers, IEEE, 2015, (to Appear

DWT-CompCNN: Deep Image Classification Network for High Throughput JPEG 2000 Compressed Documents

For any digital application with document images such as retrieval, the classification of document images becomes an essential stage. Conventionally for the purpose, the full versions of the documents, that is the uncompressed document images make the input dataset, which poses a threat due to the big volume required to accommodate the full versions of the documents. Therefore, it would be novel, if the same classification task could be accomplished directly (with some partial decompression) with the compressed representation of documents in order to make the whole process computationally more efficient. In this research work, a novel deep learning model, DWT CompCNN is proposed for classification of documents that are compressed using High Throughput JPEG 2000 (HTJ2K) algorithm. The proposed DWT-CompCNN comprises of five convolutional layers with filter sizes of 16, 32, 64, 128, and 256 consecutively for each increasing layer to improve learning from the wavelet coefficients extracted from the compressed images. Experiments are performed on two benchmark datasets- Tobacco-3482 and RVL-CDIP, which demonstrate that the proposed model is time and space efficient, and also achieves a better classification accuracy in compressed domain.Comment: In Springer Journal - Pattern Analysis and Applications under Minor Revisio

Wavelet Based Color Image Compression and Mathematical Analysis of Sign Entropy Coding

International audienceOne of the advantages of the Discrete Wavelet Transform (DWT) compared to Fourier Transform (e.g. Discrete Cosine Transform DCT) is its ability to provide both spatial and frequency localization of image energy. However, WT coefficients, like DCT coefficients, are defined by magnitude as well as sign. While algorithms exist for the coding of wavelet coefficients magnitude, there are no efficient for coding their sign. In this paper, we propose a new method based on separate entropy coding of sign and magnitude of wavelet coefficients. The proposed method is applied to the standard color test images Lena, Peppers, and Mandrill. We have shown that sign information of wavelet coefficients as well for the luminance as for the chrominance, and the refinement information of the quantized wavelet coefficients may not be encoded by an estimated probability of 0.5. The proposed method is evaluated; the results obtained are compared to JPEG2000 and SPIHT codec. We have shown that the proposed method has significantly outperformed the JPEG2000 and SPIHT codec as well in terms of PSNR as in subjective quality. We have proved, by an original mathematical analysis of the entropy, that the proposed method uses a minimum bit allocation in the sign information coding

Motion Reference Image JPEG2000 : Road surveillance Application with wireless device

WOS:000232176403013International audienceThis paper deals with a new codec based on the JPEG 2000 standard that will use a market hardware codec in order to build a road surveillance device. The developed coder consists in 4 processing steps, namely construction of a reference image, foreground extraction (ROI mask), encoding with JPEG 2000 and transmission through a wireless device. A …rst order recursive …lter is used to build a reference image that corresponds to the background image and the updated reference image is computed according to a mixture of Gaussians model. The system builds a reference image and transmits it towards a decoder through the GSM network. After the initialization phase, the reference image is updated automatically according to a Gaussian mixture model, and when the ROI can be considered as null, a piece of the updated background image is sent. We perform motion detection in order to extract a binary mask. The motion mask gives the region of interest for the system. The current image and the motion mask are coded using the ROI option of JPEG 2000 codec with a very low bit rate and transmitted towards the decoder. The complete scheme is implemented and it reaches the expected performances. We also showed how the local background image is built and updated at each frame. We presented the strategy in order to update smoothly the remote background image. The implementation runs at 5-8 frames per second on a 1.8 GHz AMD processor for 320x240 color images

Scanned Document Compression Technique

These days’ different media records are utilized to impart data. The media documents are content records, picture, sound, video and so forth. All these media documents required substantial measure of spaces when it is to be exchanged. Regular five page report records involve 75 KB of space, though a solitary picture can take up around 1.4 MB. In our paper, fundamental center is on two pressure procedures which are named as DjVU pressure strategy and the second is Block-based Hybrid Video Codec. In which we will chiefly concentrate on DjVU pressure strategy. DjVu is a picture pressure procedure particularly equipped towards the pressure of checked records in shading at high determination. Run of the mill magazine pages in shading filtered at 300dpi are compacted to somewhere around 40 and 80 KB, or 5 to 10 times littler than with JPEG for a comparative level of subjective quality. The frontal area layer, which contains the content and drawings and requires high spatial determination, is isolated from the foundation layer, which contains pictures and foundations and requires less determination. The closer view is packed with a bi-tonal picture pressure system that exploits character shape similitudes. The foundation is compacted with another dynamic, wavelet-based pressure strategy. A constant, memory proficient variant of the decoder is accessible as a module for famous web programs. We likewise exhibit that the proposed division calculation can enhance the nature of decoded reports while at the same time bringing down the bit rate