Binarization of Ancient Document Images based on Multipeak Histogram Assumption

In document binarization, text is segmented from the background. This is an important step, since the binarization outcome determines the success rate of the optical character recognition (OCR). In ancient documents, that are commonly noisy, binarization becomes more difficult. The noise can reduce binarization performance, and thus the OCR rate. This paper proposes a new binarization approach based on an assumption that the histograms of noisy documents consist of multipeaks. The proposed method comprises three steps: histogram calculation, histogram smoothing, and the use of the histogram to track the first valley and determine the binarization threshold. In our simulations we used a set of Jawi ancient document images with natural noises. This set is composed of 24 document tiles containing two noise types: show-through and uneven background. To measure performance, we designed and implemented a point compilation scheme. On average, the proposed method performed better than the Otsu method, with the total point score obtained by the former being 7.5 and that of the latter 4.5. Our results show that as long as the histogram fulfills the multipeak assumption, the proposed method can perform satisfactorily.

Satellite Imagery and In-situ Data Overlay Approach for Fishery Zonation

Remote sensing technology is useful to give a better understanding about the earth’s characteristics. SeaWiFS (sea-viewing wide field-of-view sensor) is one of remote sensors used to observe global ocean phenomena. Previous studies showed that the distribution of chlorophyll-a in the ocean indicates the presence of fish. However, only a few studies tried to directly relate the chlorophyll-a distribution obtained through interpretation of satellite imagery to in-situ data of fish distribution. This paper investigates the relation between chlorophyll-a distribution and fish-capturing points in Aceh Province sea waters using overlay image analysis. The results are useful to identify the potential fishing ground in Aceh. The profile of chlorophyll-a concentration was derived from SeaWIFS satellite imagery and fish-capturing points data was obtained from the fisherman communities of Banda Aceh, starting from June to November 2008. The results show that the chlorophyll-a profile derived from satellite imagery has a positive relationship to fish-capturing point data. The most potential fish-capturing zone in Aceh sea waters is identified at 5-8º north latitude (N) and 96-99º east longitude (E)

Studi Tentang Aplikasi Teknik Multipleks CDMA Dalam Sistem Komunikasi Serat Optik

Aplikasi serat optik sebagai media transmisi dalam sistcm . komunika_si dewasa ini telah berkembang sangat pesat. Keunggulan-keunggulan dan serat opt1k dibandingkan dengan media transmisi lai.nnya adalah : kapasitas kana! yang sangat besar, redaman yang sangat rendah dan ukuran fisiknya yang kecil dan amat ringan. Oengan memanfaatkan teknik multipleks, kapasitas kana! serat yang besar dapat dipakai untuk menyalurkan informasi secara simultan dalam jumlah yang besar pula. Salah satu metode multipleks yang baru dikembangkan untuk sistem komunikasi serat optik adalah teknik optical Code Division Multiple Acces (optical COMA). Tugas akhir ini membahas tentang aplikasi teknik multipleks COMA dalam sistem komunikasi serat optik. Akan dikaji keandal11.11 dari teknik optical COMA, dan dibandingkan dengan tcknik rnultipleks yang lcbih dulu berkembang. Pernbahasan dibatasi pada aspek prinsip operasi dan penampilarn sisternnya saja, bukan pada konfigurasi perangkat keras yang dipakai. Penyusunan tugas akhir ini lebih bersifat studi pustaka, yang pembahasannya didapat dari kajian dan analisa pelbagai literatur, terutama dari jumal-jumal ilmiah Secara umum, pembahasan dikclompokkan manjadi beberapa bagian, yaitu . unsur-unsur teknis optical COMA dan aplikasi teknik multipleks COMA dalam sistem komunikasi serat optik yang meliputi beberapa jenis optical COMA yang mulai dikembangkan -optical orthogonal codes CDA1A (OOC COMA), random carrier CDMA (RC COMA), bipolar codes CDMA (BC COMA), dan pulse position modulation CDMA (PPM COMA). Oari tugas akhir ini dapat disimpulkan, bila dibandingkan dengan teknik-teknik multipleks untuk sistem komunikasi serat optik yang telah ada, seperti TOM-POif, SOM, FDM dan WOM, optical CD~ memiliki beberapa keunggulan, antara lain : pengaksesan dapat secara asinkronus dan random, kecepatan data tinggi, jarninan sekuriti yang lebih baik dan kemampuan dalam menampung banyak user. Oari beberapa teknik optical COMA yang dibahas, penampilan sistem terbaik -diwakili oleh probability of error-nya (PE)- yang diberikan masing-masing sistem adalah : OOC COMA dengan PE sekitar 1 0"10, RC COMA dengan PE mencapai Jo·•, BC COMA dengan PE antara J0·5-IO·JJ dan PPM COMA memiliki PE sekitar I 04 . Kemampuan menampung banyak user dal111n jaringan dipcrlihatkan oleh RC COMA, di mana dengan PE sekitar to·• mampu rnenampung hingga 17000 user aktif

Improved Model of the Selection with Soft- and Hard-Combining Decoding Strategies for Multi-User Multi-Relay Cooperative Networks

In a wireless cooperative network, system reliability can be improved by introducing network coding (NC) for transmitting data packets from user to destination through relay nodes. At the destination, a decoding strategy is required to recover the original data packets. The use of NC in cooperative networks has been intensively studied in previous works in terms of the conventional model for two users and a single relay in a network. However, the network model cannot act as a virtual multiple-input multiple-output system, and a multi-user multi-relay network model could be used in a real system. Therefore, this paper proposes an improved model of two network decoding strategies, selection with soft combining (SSC) and selection with hard combining (SHC), for multi-user multi-relay cooperative networks. Users are classified based on their channel conditions, with better signal-to-noise (SNR) ratio sources being viewed as strong users, and others as weak or moderate users in the decoding strategies. To evaluate the performance of the proposed model, we first derive the bit error probability expressions for each strategy as a function of SNR and then evaluate the performance using numerical simulation for a Rayleigh fading channel. Simulation results show that SSC outperforms SHC. Furthermore, the improvement in network performance is achieved either by having a higher modulation level or using incremental relaying as the signal reception method at the destination

The Existence of Radio Republik Indonesia Banda Aceh in Educating Disaster Risk Reduction Efforts

Radio is one of the media still used by the public either for having entertainment or gaining information. Amid the rapid growth of television and internet, radio is still exhibiting its existence. Radio’s involvement on the efforts of educating Disaster Risk Reduction (DRR) to the public is crucial because it can be accessed conveniently in variety circumstances. This study focused on examining how the existence of Radio RepublikIndonesia (RRI) Banda Aceh in educating DRR efforts for the public. It discussed about how the people obtain the DRR education through some radio programs concerning to DRR. RRI Banda Aceh was chosen because it is the only one government owned radio in Banda Aceh that is responsible on educating the public through the broadcasting contents. This study was conducted by using a qualitative method. The data were collected by means of interviewing the leaders of RRI Banda Aceh and observing the recording of the radio broadcasted contents related to the DRR. This study, eventually, found that the existence of RRI Banda Aceh in educating DRR efforts was manifested in three different ways such as broadcasting disaster news, talk-shows, and public service announcements. Those three ways had their own advantages and disadvantages

Comparison of Several Fusion Rule Based on Wavelet in The Landsat ETM Image

Remote sensing image quality and the improvement of remote sensing image position accuracy on Landsat ETM satellite is highly needed in term of remote sensing. Therefore, it is required one way or more to obtain the quality and accuracy of the image which uses image processing. Fusion technique is one of the image processing example that is using an existing descriptions to catch the result of image that can provide better information in the content. In this final task, multispectral images have high spectral information content and low spatial, also high spatial information content in panchromatic image that it is needed to do the image fusion in order to have a spectral information content and high spatial to compare the performance of some fusion rules wavelet-based on the multispectral image fusion and panchromatic imagery. The image used is Landsat ETM. The performance of image fusion rules is compared with the mean gradient parameters, mutual information, mean square error and correlation coefficient. Based on the test results, image fusion has an influence on the information content of multispectral imagery and panchromatic imagery, which is the spectral and spatial information content are getting better, the ratio of the 6 image fusion rules have inconsistent values of the three image testings to the mean gradient parameters, mutual information and mean square error and the results of image fusion of the fifth fusion rules on the correlation coefficient have a consistent value of the three image testings

Penggunaan Gray Level Co-Occurance Matrix Dari Koefisien Aproksimasi Wavelet untuk Deteksi Cacat Tekstil

Pendeteksian cacat tekstil saat ini masih dilakukan secara manualmengakibatkan seseorang sulit mendeteksi lebih dari 60% dari cacat yang ada.Untuk itu, penelitian ini menerapkan metode deteksi cacat tekstil secara otomatismenggunakan Gray Level Co-Occurance Matrix (GLCM) dari koefisienaproksimasi wavelet yang bertujuan untuk mengevaluasi analisis kinerja metode.Tahapannya, sampel citra tekstil dibagi menjadi delapan bagian untukmendapatkan tekstur cacat yang lebih jelas. Bagian tersebut didekomposisikedalam dua level. GLCM dihitung dari koefisien aproksimasi wavelet level satudan dua untuk dijadikan fitur. Penelitian ini dilakukan empat set simulasi citradengan orientasi latar berbeda. Setiap set terdiri dari satu citra noncacat dan duajenis citra cacat. Setiap bagian citra noncacat dihitung jaraknya dengan semuabagian pada citra cacat pertama dan kedua menggunakan jarak euclidean. Hasilsimulasi menunjukkan bahwa GLCM dari koefisien aproksimasi wavelet levelkedua mampu mendeteksi lebih dari 70% dari cacat yang ada

Fine Tuning CNN Pre-trained Model Based on Thermal Imaging for Obesity Early Detection

Obesity is a complex disease that causes serious impact health, such as diabetes mellitus, cardiovascular disease, cancer, and stroke. An early obesity diagnosis/ detection method is required to prevent the increasing number of obese people. This study aims to: (i) fine-tune the pre-trained Convolutional Neural Network (CNN) models to build an early detection of obesity and (ii) evaluate the model performance in terms of classifying performance, computation speed, and learning performance. The thermal images acquisition procedure was conducted with 18 normal subjects and 15 obese subjects to build a thermal images dataset of obesity. Pre-trained CNN models: VGG19, MobileNet, ResNet152V, and DenseNet201 were modified and trained using the acquired dataset as the input. The training results show that the DenseNet201 model outperformed other models regarding classifying accuracy: 83.33 % and learning performances. At the same time, the MobileNet model outperformed other models in terms of computation speed with training elapsed time: 12 seconds/epoch. The proposed DenseNet201 model was suitable for implementation as an early screening system of obesity for health workers or physicians. Meanwhile, the proposed MobileNet model was suitable for mobile applications' early detection/diagnosis of obesity

Moment invariant-based features for Jawi character recognition

Ancient manuscripts written in Malay-Arabic characters, which are known as "Jawi" characters, are mostly found in Malay world. Nowadays, many of the manuscripts have been digitalized. Unlike Roman letters, there is no optical character recognition (OCR) software for Jawi characters. This article proposes a new algorithm for Jawi character recognition based on Hu’s moment as an invariant feature that we call the tree root (TR) algorithm. The TR algorithm allows every Jawi character to have a unique combination of moment. Seven values of the Hu’s moment are calculated from all Jawi characters, which consist of 36 isolated, 27 initial, 27 middle, and 35 end characters; this makes a total of 125 characters. The TR algorithm was then applied to recognize these characters. To assess the TR algorithm, five characters that had been rotated to 90o and 180o and scaled with factors of 0.5 and 2 were used. Overall, the recognition rate of the TR algorithm was 90.4%; 113 out of 125 characters have a unique combination of moment values, while testing on rotated and scaled characters achieved 82.14% recognition rate. The proposed method showed a superior performance compared with the Support Vector Machine and Euclidian Distance as classifier