Alexandre Zaghetto

Segmentation-Driven Compound Document Coding Based on H.264/AVC-INTRA

In this paper, we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e., composed of text, graphics, and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/AVC quantization parameter on a macroblock by macroblock basis, i.e., we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.

An H.264/AVC to HEVC video transcoder based on mode mapping

The emerging video coding standard, HEVC, was developed to replace the current standard, H.264/AVC. However, in order to promote inter-operability with existing systems using the H.264/AVC, transcoding from H.264/AVC to the HEVC codec is highly needed. This paper presents a transcoding solution that uses machine learning techniques in order to map H.264/AVC macroblocks into HEVC coding units (CUs). Two alternatives to build the machine learning model are evaluated. The first uses a static training, where the model is built offline and used to transcode any video sequence. The other uses a dynamic training, with two well-defined stages: a training stage and a transcoding stage. In the training stage, full re-encoding is performed while the H.264/AVC and the HEVC information are gathered. This information is then used to build a model, which is used in the transcoding stage to classify the HEVC CU partitioning. Both solutions are tested with well-known video sequences and evaluated in terms of rate-distortion (RD) and complexity. The proposed method is on average 2.26 times faster than the trivial transcoder using fast motion estimation, while yielding a RD loss of only 3.6% in terms of bitrate.

CQR codes: Colored quick-response codes

This paper proposes a new way to store/transmit information using a Colored QR Code structure. Instead of using only black and white modules, the proposed code is designed to employ 5 different RGB colors (red, green, blue, black and white), which enables twice as much storage capacity compared to traditional binary QR Codes. Reed-Solomon error-correcting code with a theoretical correction capability of 38.41% is also applied. In our experiments, each Colored QR Code in the test set is printed, scanned using a 3.2 megapixel digital camera and decoded. We show that the proposed scheme can consistently decode 1024 bits of information stored on a 1.3 cm × 1.3 cm printed area.

MRC Compression of Compound Documents Using Threshold Segmentation, Iterative Data-Filling and H.264/AVC-INTRA

The Mixed Raster Content (MRC) ITU document compression standard (T.44) specifies a multi-layer representation of a compound document. It is expected that higher compression can be achieved if more efficient compression standards are used to compress each layer. In this paper we present an MRC compound document codec that uses H.264/AVC operating in INTRA mode to encode Background/Foreground layers and JBIG2 to encode the binary Mask layer. We also present a threshold-based layer segmentation algorithm and an iterative data-filling algorithm for redundant regions. The result is an unrivaled performance for compressing compound documents as demonstrated by our experiments.

Two-dimensional compression of surface electromyographic signals using column-correlation sorting and image encoders

We present a new preprocessing technique for two-dimensional compression of surface electromyographic (S-EMG) signals, based on correlation sorting. We show that the JPEG2000 coding system (originally designed for compression of still images) and the H.264/AVC encoder (video compression algorithm operating in intraframe mode) can be used for compression of S-EMG signals. We compare the performance of these two off-the-shelf image compression algorithms for S-EMG compression, with and without the proposed preprocessing step. Compression of both isotonic and isometric contraction S-EMG signals is evaluated. The proposed methods were compared with other S-EMG compression algorithms from the literature.

Scanned Document Compression Using Block-Based Hybrid Video Codec

This paper proposes a hybrid pattern matching/transform-based compression method for scanned documents. The idea is to use regular video interframe prediction as a pattern matching algorithm that can be applied to document coding. We show that this interpretation may generate residual data that can be efficiently compressed by a transform-based encoder. The efficiency of this approach is demonstrated using H.264/advanced video coding (AVC) as a high-quality single and multipage document compressor. The proposed method, called advanced document coding (ADC), uses segments of the originally independent scanned pages of a document to create a video sequence, which is then encoded through regular H.264/AVC. The encoding performance is unrivaled. Results show that ADC outperforms AVC-I (H.264/AVC operating in pure intramode) and JPEG2000 by up to 2.7 and 6.2 dB, respectively. Superior subjective quality is also achieved.

Improved layer processing for MRC compression of scanned documents

The Mixed Raster Content (MRC) document compression is a well documented standard. Its efficiency for representing sharp text and graphics over a background has been extensively presented. Scanned documents, however, are difficult to be dealt with because of soft transitions. In one of our previous works we presented a pre/post-processing algorithm for MRC compression of scanned images that sharpens the edges, before compression, and softens it again, after reconstruction. The present paper uses the same basic idea but describes three new features that improve, in a rate-distortion sense, the compression performance. First, the real bitrate is used to determine the pre/post-processing parameters. Second, the Mask layer and the edge sharpening/softening map have their quality improved and, third, layer resolution change has been explored. Experimental results show that the method not only provides higher subjective quality, but it can yield up to 2.5 dB gains in PSNR against single coder approaches, in the compression ranges of interest.

Compression of touchless multiview fingerprints

Recently, touchless multiview fingerprinting technology has been proposed as an alternative to overcome the intrinsic problems of traditional contact-based systems. Nevertheless, compression of this kind of signal has not been fully evaluated and standardized. This paper investigates the comparative performance of several encoders for this data, namely WSQ, JPEG2000, H.264/AVC and MMP. Experimental results show that WSQ encoder, which is the current compression standard for contact-based fingerprints, is objectively outperformed by all others. In particular, MMP, which achieved the best results, outperforms WSQ by up to 4 dB.

High quality scanned book compression using pattern matching

This paper proposes a hybrid approximate pattern matching/transform-based compression engine. The idea is to use regular video interframe prediction as a pattern matching algorithm that can be applied to document coding. We show that this interpretation may generate residual data that can be efficiently compressed by a transform-based encoder. The novelty of this approach is demonstrated by using H.264/AVC, the newest video compression standard, as a high quality book compressor. The proposed method uses segments of the originally independent scanned pages of a book to create a video sequence, which is encoded through regular H.264/AVC. Results show that the proposed method outperforms AVC-I (H.264/AVC operating in pure intra mode) and JPEG2000 by up to 4 dB and 7 dB, respectively. Superior subjective quality is also achieved.

Using H.264/AVC-Intra for Segmentation-Driven Compound Document Coding

In this paper we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e. composed of text, graphics and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/ AVC quantization parameter on a macroblock by macroblock basis, i.e. we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.