MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

/pdf/information-security-management-handbook-ivwx8fbile.pdf

Information Security Management Handbook

Thank you for reading lte and the evolution to 4g wireless design and measurement challenges. Maybe you have knowledge that, people have search hundreds times for their favorite books like this lte and the evolution to 4g wireless design and measurement challenges, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they cope with some malicious bugs inside their desktop computer.

Lte And The Evolution To 4g Wireless Design And Measurement Challenges

/pdf/data-mining-concept-aplications-and-techniques-574zeqwdyg.pdf

Data Mining: Concept, Aplications and Techniques

Grossman's endodontic practice

Based on the livestock size are divided into two parts, where firstly the small one and the other the large one. Whereas the small one consists of poultry, sheep, goats, rabbit, etc. Measuring in the small animal weight could be directly weight, because very easier than the large one. To measure the weight of large animal, especially beef cattle, there are some differences. The body length, chest circumstance, height and width of this animal is could be estimated. Any kind of method in measuring the weight of livestock are calculated systematically. However the measurement is not entirely accurate when predicting the weight of beef cattle life. That is why, it is possibly to get a simply method to estimate the weight of beef cattle meat The technical information for analyzing of beef cattle weight which call a digital image processing could be used, because it can analyze via photograph system. By using digital image processing with specific algorithms could be recognized certain objects easily. The accurate yield depend on the photograph capability estimation on body length, chest circumstance, height, and the width of beef cattle itself.

Beef cattle weight determine by using digital image processing

Technology used to hide secret message in a communication called Steganography. Secret message can be text, image or any file that can be converted into binary. This secret message inserted into cover file which can be in form of image, sound or video, basiccaly cover file must be bigger than the secret message in size. Many methods have been proposed on how to hide secret messages in a cover file. These method include spatial domain which work on bit instead of statistically on cover file. Least Significant Bit have been long known as the simplest steganography embedding method. In this research we proposed a method of LSB with enhanced technique to increase security. To extract secret message from cover file one should have particular stego key that describe the location of the message and how to reconstruct them. We utilize a people detection method as a stego key since most of video footage involving human figure, from personal video footage, movie video or security camera recording. While maintaining the appearance of the cover video from arousing suspiciousness, the size of secret message that can be embedded to be one point of consideration.

Enhanced LSB Steganography with people detection as stego key generator

Abstrak Tingginya minat masyarakat terhadap susu, membuat para produsen melakukan inovasi agar mendapatkan keuntungan yang lebih dengan menurunkan kualitas asli dari susu sapi. Misalnya menambahkan bahan tambahan yang dapat merusak nilai gizi dari susu dengan dicampur air agar volumenya lebih banyak. Cara umum dalam membedakan kualitas susu, yaitu dari aroma dan rasa, namun hal tersebut tidak efektif karena indra perasa setiap orang dapat berbeda. Pada era masa kini diperlukan teknologi yang dapat membedakan susu murni dengan susu yang sudah dicampur bahan lain. Penelitian dilakukan dengan mengidentifikasi kualitas kesegaran susu sapi melalui pengolahan citra digital menggunakan metode Watershed, dimana proses ekstraksi ciri menggunakan Local Binary Pattern serta diklasifikasikan menggunakan Learning Vector Quantization. Sistem tersebut telah diaplikasikan melalui penggunaan perangkat lunak Matlab dengan mengidentifikasi dan mengklasifikasikannya pada tekstur susu sapi. Pengambilan data dilakukan dengan cara mengambil sampel susu sapi murni dan sampel susu sapi yang dicampur air sebanyak 25%, 50%, dan 75%. Hasil penelitian identifikasi kualitas kesegaran susu diperoleh tingkat akurasi sebesar 92.5% dan waktu komputasi 0.4791 detik. Kata kunci: Susu Sapi, Watershed, Learning Vector Quantization Abstract The high public interest of milk which give many benefits for human body, urge the producers for doing an innovation to get more profit by lowered the quality of the milk adding an additional substance to the milk can impair the quality of the milk itself. A general way to distinguish whether the quality of the milk is good or not is from its aroma and taste. On the other hand, this kind of way is not effective. In this era of technology, it is needed a kind of technology which can distinguish whether the milk is pure or not. Research done by identifying the quality of fresh cow's milk through digital image processing using Watershed method, where the extraction process characteristics using Local Binary Pattern and classified using Learning Vector Quantization. The system has been applied through the use of Matlab software by identifying and classifying on texture of cow's milk. Data retrieval is done by taking a sample of pure cow's milk and cow's milk samples were mixed in the water as much as 25%, 50%, and 75%. The research of identification the quality freshness obtained accuracy of 92.5% and computational time 0.4791 seconds. Keywords: Cowâ€™s milk, Watershed, Learning Vector Quantization

/pdf/identifikasi-kualitas-kesegaran-susu-sapi-melalui-pengolahan-3h0e17j9wp.pdf

Identifikasi Kualitas Kesegaran Susu Sapi Melalui Pengolahan Citra Digital Menggunakan Metode Watershed Dan Klasifikasi Learning Vector Quantization (lvq)

Abstrak Aksara Bali merupakan salah satu tulisan daerah yang digunakan di Indonesia. Untuk membaca aksara Bali tidaklah mudah. Hal ini disebabkan karena kesulitan untuk mengenali bentuk atau pola dari suku kata dasar aksara tersebut. Suku kata dasar aksara Bali hampir memiliki struktur yang sama, sehingga di dalam pembacaannya akan menemukan kesulitan mengidentifikasi suku kata dasar. Penelitian ini dibuat dengan tujuan untuk membuat suatu sistem yang mampu mengenali pola dari aksara Bali dimana aksara Bali yang digunakan adalah aksara Bali dasar. Sistem ini menggunakan teknik Local Binary Pattern (LBP) untuk ekstraksi cirinya. Salah satu sifat paling penting dari operator LBP ialah kesederhanaan perhitungannya, memiliki waktu komputasi yang lebih cepat, dan sifatnya yang invarian terhadap perubahan fotometri dari objek yang sama, dikarenakan LBP merupakan ukuran intensitas relatif suatu piksel dengan intensitas piksel disekitarnya. LBP didefinisikan sebagai perbandingan nilai piksel pada pusat citra dengan nilai piksel disekelilingnya sehingga diperoleh nilai biner pada matriks tersebut. Hasil dari LBP ini dijadikan masukan pada proses klasifikasi citra yang menggunakan Support Vector Machine dan K-Nearest Neighbor. Keunggulan dari metode KNN adalah tangguh terhadap data latih yang memiliki banyak noise dan efektif apabila data latihnya berukuran besar, sedangkan metode klasifikasi SVM mempunyai beberapa kelebihan, diantaranya bisa memodelkan dan mengklasifikasikan hubungan antar variabel tanpa perlu asumsi yang ketat, efisien, dan interpretasinya mudah. Pada penelitian ini juga membandingkan proses klasifikasi antara metode Support Vector Machine dengan K- Nearest Neighbor. Hasil dari simulasi yang dilakukan sistem dapat mengenali Aksara Bali dengan tingkat akurasi tertinggi adalah 74,6%, ddengan waktu komputasi rata-rata sistem sebesar 2,3203 detik. Kata kunci : Aksara Bali, Local Binary Pattern (LBP), Support Vector Machine (SVM), K-Nearest Neighbor (KNN).

/pdf/pengenalan-aksara-bali-dengan-metode-local-binary-pattern-3xumd6bepm.pdf

Pengenalan Aksara Bali Dengan Metode Local Binary Pattern

Information exchange between sender and receiver becomes very fast and easy. The quality of message transmission, especially the security, must be noticed. Data hiding is important for securing message. It can be done using cryptography and steganography. This paper describes the result of investigation on image steganography system using secret grayscale image and RGB image as a cover. Before the secret image is embedded into the cover, the encryption process is done to provide a more reliable security. The encryption method used is based on rubik's cube principle, by moving the pixels position in a digital image. The steganography uses LSB substitution method that works in spatial domain. The objective of this scheme is to obtain a high quality hidden secret image in order to keep message secret. Finally, effectiveness of the proposed scheme is tested using histogram analysis, Avalanche effect, Brute-Force attack, visual attack, statistical attack of Chi-Square analysis, and size and embedding position differences analysis.

Bambang Hidayat

Papers

Beef cattle weight determine by using digital image processing

Enhanced LSB Steganography with people detection as stego key generator

Identifikasi Kualitas Kesegaran Susu Sapi Melalui Pengolahan Citra Digital Menggunakan Metode Watershed Dan Klasifikasi Learning Vector Quantization (lvq)

Pengenalan Aksara Bali Dengan Metode Local Binary Pattern

Digital image steganography with encryption based on rubik's cube principle