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Music identification is widely regarded as a solved problem for music searching in quiet environments, but its performance tends to degrade in TV broadcast audio owing to the presence of dialogue or sound effects. In addition, constructing an accurate dataset for measuring the performance of background music monitoring in TV broadcast audio is challenging. We propose a framework for monitoring background music by automatic identification and introduce a background music cue sheet. The framework comprises three main components: music identification, music-speech separation, and music detection. In addition, we introduce the Cue-K-Drama dataset, which includes reference songs, audio tracks from 60 episodes of five Korean TV drama series, and corresponding cue sheets that provide the start and end timestamps of background music. Experimental results on the constructed and existing datasets demonstrate that the proposed framework, which incorporates music identification with music–speech separation and music detection, effectively enhances TV broadcast audio monitoring.

Music identification is widely regarded as a solved problem for music searching in quiet environments, but its performance tends to degrade in TV broadcast audio owing to the presence of dialogue or sound effects. In addition, constructing an accurate dataset for measuring the performance of background music monitoring in TV broadcast audio is challenging. We propose a framework for monitoring background music by automatic identification and introduce a background music cue sheet. The framework comprises three main components: music identification, music–speech separation, and music detection. In addition, we introduce the Cue‐K‐Drama dataset, which includes reference songs, audio tracks from 60 episodes of five Korean TV drama series, and corresponding cue sheets that provide the start and end timestamps of background music. Experimental results on the constructed and existing datasets demonstrate that the proposed framework, which incorporates music identification with music–speech separation and music detection, effectively enhances TV broadcast audio monitoring. [ABSTRACT FROM AUTHOR]

To realize the real-time monitoring of the cotton precision seeding operation process and improve the intelligence level of cotton precision planters, based on automatic color matching detection technology and visualization technology, this study designs a monitoring system for the sowing quality of cotton precision planters. The monitoring system is based on the double-silo turntable type cotton vertical disc hole seed metering device as the research carrier, and is composed of a missed seeding monitoring module and a visualization module. Among them, the missed seeding monitoring module includes an incremental rotary encoder, color code electric eye color fiber optic sensor, color code sensor amplifier, etc.; the visualization module includes data acquisition module, industrial computer, and so on. The missing seeding monitoring module is installed on the seed spacer of the cotton precision seed metering device. It uses Labview software for graphical programming and is equipped with a multi-functional industrial computer. It realizes the monitoring of parameters such as the number of sowings, the number of missed sowings, the speed of the hole seeder, the forward speed of the machine, and the sowing area. The results of the bench test and field test of the sowing monitoring system showed that the accuracy rate of the system's broadcast monitoring was over 93%, and the accuracy rate of missed broadcast monitoring was over 91%. The system solved the technical problem that cotton film-laying and sowing were not easy to detect. It could accurately detect the quality of cotton sowing in real time and meet the actual requirements of sowing monitoring. [ABSTRACT FROM AUTHOR]

To realize the real-time monitoring of the cotton precision seeding operation process and improve the intelligence level of cotton precision planters, based on automatic color matching detection technology and visualization technology, this study designs a monitoring system for the sowing quality of cotton precision planters. The monitoring system is based on the double-silo turntable type cotton vertical disc hole seed metering device as the research carrier, and is composed of a missed seeding monitoring module and a visualization module. Among them, the missed seeding monitoring module includes an incremental rotary encoder, color code electric eye color fiber optic sensor, color code sensor amplifier, etc.; the visualization module includes data acquisition module, industrial computer, and so on. The missing seeding monitoring module is installed on the seed spacer of the cotton precision seed metering device. It uses Labview software for graphical programming and is equipped with a multi-functional industrial computer. It realizes the monitoring of parameters such as the number of sowings, the number of missed sowings, the speed of the hole seeder, the forward speed of the machine, and the sowing area. The results of the bench test and field test of the sowing monitoring system showed that the accuracy rate of the system’s broadcast monitoring was over 93%, and the accuracy rate of missed broadcast monitoring was over 91%. The system solved the technical problem that cotton film-laying and sowing were not easy to detect. It could accurately detect the quality of cotton sowing in real time and meet the actual requirements of sowing monitoring.

Considered the authentication of video clips applied in broadcast monitoring, a new robust hashing algorithm for video was proposed based on the 3D wavelet transform （3D DWT）. The new proposed algorithm could realize the authentication of video clips by using the embedded watermark information created by the hash value and the watermark identifier. This new robust video watermark algorithm could also be applied in the security of broadcast monitoring. Based on the academic analysis and experimental results, the new proposed algorithm has good security and robust performance.

when people are attaching or interesting in something, usually they are trying to interact with it frequently. Music is attached to people since the day of they were born. When music repository grows, people faced lots of challenges such as finding a song quickly, categorizing, organizing and even listening again when they want etc. Because of this, people tend to find electronic solutions. To index music, most of the researchers use content based information retrieval mechanism since content based classification doesn't need any additional information rather than audio features embedded to it. As well as it is the most suitable way to search music, when user don't know the meta data attached to it, like author of the song. The most valuable application of this audio recognition is copyright infringement detection. Throughout this survey we will present approaches which were proposed by various researchers to detect, recognize music using content base mechanisms. And finally we will conclude this by analyzing the current status of this era. [ABSTRACT FROM AUTHOR]

Proposing a novel approach for monitoring songs for the radio broadcasting channels is very important for the interest of singers, writers and musicians in the musical industry. Singers, writers and musicians have a claim to intellectual property rights for their songs broadcast over all the radio channels. According to this intellectual property rights act singers, writers and musicians should be paid for their songs broadcast over all the radio channels. Therefore we propose a real time audio monitoring approach to solve this problem which includes our own audio recognition algorithm. It is easy to recognize a song, when you provide the original high quality blueprint of the song as input. But we can't expect such kind of audio input from radio channels since lots of transformations are possible before reaching the end user or listener. For example, adding environmental effects such as noise, adding commercials on the song as watermarks, playing more than one song as a chain without adding any silence between them, playing a part of the song, playing same song in various speeds and so on. These transformations cause change in the uniqueness of particular song and make the problem even more difficult. The algorithm we proposing is resistant to noise and distortion as well as it is capable of recognizing short segment of song when broadcasting over the radio channels. At the end of the processing our system generates a descriptive report including title of the song, singer of the song, writer of the song, composer of the song, number of times it was played and when it was played for all songs for a particular period for all radio broadcasting channels. We evaluate our system against various types of real time scenarios and achieved overall higher level of accuracy (96%) at the end. [ABSTRACT FROM AUTHOR]

The Internet presents a problem for the protection of intellectual property. Those who create content must be adequately compensated for the use of their works. Rights agencies who monitor the use of these works exist in many juristictions. In the traditional broadcast environment this monitoring is a difficult task. With Internet Protocol Television (IPTV) and Next Generation Networks (NGN) this situation is further complicated. In this work we focus on Digitally Watermarking next generation media broadcasts. We present a framework which provides the ability to monitor media broadcasts that also utilises a Public Key Infrastructure (PKI) and Digital Certificates. Furthermore, the concept of an independent monitoring agency, that would operate the framework and act as an arbiter, is introduced. We evaluate appropriate short signature schemes, suitable Watermarking algorithms and Watermark robustness. Finally, the application of the proposed framework in other related scenarios is discussed. [ABSTRACT FROM AUTHOR]

Identification and verification of a video clip via its fingerprint find applications in video browsing, database search and security. For this purpose, the video sequence must be collapsed into a short fingerprint using a robust hash function based on signal processing operations. We propose two robust hash algorithms for video based both on the discrete cosine transform (DCT), one on the classical basis set and the other on a novel randomized basis set (RBT). The robustness and randomness properties of the proposed hash functions are investigated in detail. It is found that these hash functions are resistant to signal processing and transmission impairments, and therefore can be instrumental in building database search, broadcast monitoring and watermarking applications for video. The DCT hash is more robust, but lacks security aspect, as it is easy to find different video clips with the same hash value. The RBT based hash, being secret key based, does not allow this and is more secure at the cost of a slight loss in the receiver operating curves [ABSTRACT FROM PUBLISHER]

A new framework for data embedding in audio is proposed. The basic idea of the algorithm is to change the length of the intervals between salient points of the audio signal to embed data. The intervals are quantized and the data is embedded in the quantization indices. In our particular implementation, we use the wavelet extrema of the signal envelope as the salient points. We propose novel ideas for practical implementation that can be used by other data embedding schemes as well. The algorithm is robust to common audio processing operations, e.g., mp3 lossy compression, low pass filtering, sampling rate conversion, and time-scale modification (TSM). The perceptual quality of the audio signal after embedding the data depends on the techique used for TSM. [ABSTRACT FROM AUTHOR]

In this paper, to automate broadcast monitoring, which is typified by the verification of the transmission of the material ID code of a commercial message (CM) or program, the authors propose a watermarking scheme without reference images, which does not require a reference image when the watermark sequence is extracted. By embedding a watermark sequence formed by using standard normal random numbers after discretizing the embedding-target coefficients in the DCT domain, the proposed technique makes a reference image unnecessary when the watermark sequence is extracted. In addition, since the proposed technique enables a watermark image having the desired image quality (PSNR) to be achieved for any image, it has the advantage that the image quality can always be maintained regardless of the image. Therefore, the same procedure can always be used to embed the watermark sequence in a full-motion video image without obtaining parameters for each image and to extract that watermark sequence without using a reference image. The authors used simulations to verify that an image quality of at least 56 dB, which is the HDTV digital VTR guideline, can be maintained even in the watermarked image, that the watermark sequence can be extracted without using a reference image, and that the proposed technique is robust with respect to MPEG. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 87(9): 22–32, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.20101 [ABSTRACT FROM AUTHOR]

We propose a novel algorithm for high-quality data embedding in audio. The algorithm is based on changing the relative length of the middle segment between two successive maximum and minimum peaks to embed data. Spline interpolation is used to change the lengths. To ensure smooth monotonic behavior between peaks, a hybrid orthogonal and nonorthogonal wavelet decomposition is used prior to data embedding. The possible data embedding rates are between 20 and 30 bps.However, for practical purposes, we use repetition codes, and the effective embedding data rate is around 5 bps. The algorithm is invariant after time-scale modification, time shift, and time cropping. It gives high-quality output and is robust to mp3 compression. [ABSTRACT FROM AUTHOR]

We propose a novel algorithm for high-quality data embedding in audio. The algorithm is based on changing the relative length of the middle segment between two successive maximum and minimum peaks to embed data. Spline interpolation is used to change the lengths. To ensure smooth monotonic behavior between peaks, a hybrid orthogonal and nonorthogonal wavelet decomposition is used prior to data embedding. The possible data embedding rates are between 20 and 30 bps. However, for practical purposes, we use repetition codes, and the effective embedding data rate is around 5 bps. The algorithm is invariant after time-scale modification, time shift, and time cropping. It gives high-quality output and is robust to mp3 compression.