Identifikasi Otomatis Anemia pada Citra Sel Darah Merah Berbasis Komputer

Intisari---Penelitian inimengusulkan sebuah algoritma berbasis komputer sebagai alat bantupemeriksaan laboratorium dalam mengidentifikasi anemia secara efisien dan denganbiaya yang murah. Algoritma yang diusulkan terdiri dari tiga proses utama, yaitu pengolahan citra, ekstraksi fitur, dan proses identifikasi. Proses pengolahan citra dilakukan dalam dua tahap, yakni ­pre-processing dan segmentasi. Pada proses ekstraksi fitur, dilakukan penyusunan vektor fitur berdasarkan keluaran dari proses pengolahan citra. Vektor fitur ini menjadi masukan dalam proses identifikasi otomatis anemia dannon-anemia pada citra sel darah merah menggunakan metode K-Means. Algoritma yang diusulkan digunakan pada 92 buah citra sel darah merah, dengan rincian 52 buah citra terindikasi anemia, dan 40 buah citra kategori non-anemia.Hasil identifikasi untuk seluruh citra sel darah merah divalidasi dengan membandingkan keluaran dari K-Means dengan hasil identifikasi oleh tenaga medis. Dari proses validasi, didapatkan nilai akurasi sebesar 94.5%, yang menunjukkan bahwa algoritma yang diusulkan mampu mengidentifikasi anemia dan non-anemia secara efektif.Kata kunci--- Anemia, Citra sel darah merah, Idenfikasi, K-Means, Komputer                                      Abstract--- This research workproposes a computerized algorithmto perform an efficient and low-cost anemia identification. Our algorithm consists of three main phases, namely image processing, feature extraction, and identification. Theimage processing phase is done in two steps, the image pre-processing and segmentation steps.The feature vector of all images is constructed based on the pixel intensity values of the segmented images. The constructed feature vector becomes the input of the identification phase, which is performed using K-Means method. The proposed algorithm is applied on 92 red blood cell images, consist of 52 and 40 anemia and non-anemia images, respectively. The identification results are validated by comparing them to those of the medical staff. The achieved accuracy for the validation process is 94.5%, indicating that our proposed algorithm is able to identify anemia and non-anemia effectively.Keywords--- Anemia, Computer, Identification, K-Means, Red Blood Cell Images

Detection of Cervical Cancer Based on Learning Vector Quantization and Wavelet Transform

Cervical cancer has became the common women dsease in the world. Mostly, cervical cancer has been already known lately, because it is very dificult to detect this in early stage. In this work, a computer based software using Learning Vector Quantization (LVQ) has been designed as the early cervical cancer detection aid tool. There are six methods before the detection is performed, namely preprocessing, contrast stretching, median filtering, morphology operation, image segmentation, and Wavelet Transform based feature extraction. In tihis work, 73 cervical cell images that consist of 50 normal images and 23 cancer images are used. 35 normal images and 14 cancer images are used to train the LVQ. Then, 23 normal images and 9 cancer images are used in the testing process. Our results show 88,89 % cancer image can be detected correctly (sensitivity), 100 % normal image can be detected corerctly (specificity), and 95,83 % for overall detection (accuracy)

Retinal Blood Vessel Segmentation as a Tool to Detect Diabetic Retinopathy

The retina is an important part of the eye for humans. Inbesides its main function as part of the sense of sight, in the worldmedically, the retina after an image can be used to detect a numberdiseases, such as diabetic retinopathy. To detect a number of diseases,Retinal digital images taken using a digital fundus camera are used.In detecting diabetic retinopathy, digital images are neededsegmented retina. Nevertheless, automatic segmentation of digital imagesthe retina is a complex work, given the presence of artifactsas well as noise on the retinal digital image, evenly illuminated, intensitylow, low contrast, and varying lengths of retinal blood vessels.In this research, a blood vessel segmentation software system has been designed through three stagesimage processing, namely (i) preprocessing, (ii) improving image quality, (iii) andsegmentation of retinal blood vessels. With three image processing stages, the performance value is obtained, i.e. 84.62

Implementation of GLCM for Features Extraction and Selection of Batik Images

Batik is a craft that has high artistic value and has been a part of Indonesian culture (especially Java) for a long time. Batik cloth in Indonesia has various types of batik textures, batik cloth colors, and batik fabric patterns that reflect the regional origins of the batik cloth. Regarding the image of batik, the texture feature is an important feature because the ornaments on the batik cloth can be seen as different texture compositions. Besides batik motifs, also influenced by the shape characteristics that become parts of each batik motif. This research will add insight and knowledge to understand batik patterns based on the characteristics of batik motifs, namely texture. There are five batik motifs used, namely inland solo batik, semarang coastal batik, sidhomukti batik, parangklithik batik, and sidhodrajat batik. Initially preprocessing is done by cropping and grayscalling. Of the five image motifs, a cropping process is carried out for each motif. The next step is feature extraction. The features of GLCM were selected in this study. From the features contained in the GLCM, in this study four features were chosen, namely contrast, energy, correlation, and homogeneity. The final step is the selection or selection of features. The result of the feature selection of the four features carried out feature extraction are energy and homogeneity

Verifikasi Citra Tanda Tangan Berbasis Perceptron

A signature has become an important human attribute, which can represent personal information. Human signatures are widely used to authorize documents, both paper-based as well as electronic-based ones. However, such authorization still poses various privacy issues, such as signature duplication and forgeries. These may not be easy to be addressed, particularly when involving many documents. Hence, advanced procedures are required to verify the signature authenticity. In this paper, we propose a new method for automatic signature verification based on the digitalized signature images. The method comprises successive image processing techniques, such as cropping, resizing, gray-scaling and thresholding. The binary images as the results of thresholding serve as the features of the signatures and are used to train a single layer Perceptron neural network. The experiment in this paper uses 42 digitalized signatures images, collected from two subjects. The obtained images are divided into the training and testing sets, in which the training and testing sets comprise 14 and 28 images, respectively. In the experiment, the proposed method produces the average training and testing accuracies of 100% and 98.85%, respectively. These indicate that the proposed method is reliable for practical applications

Performance Analysis of Lung Cancer Diagnosis Algorithms on X-Ray Images

Among several types of cancer, lung cancer is regarded as one of the most common and serious. In this respect, early diagnosis is required and beneficial to reduce mortalities caused by this type of cancer. Such diagnosis is typically performed by doctors through manual examinations on X-Ray images. However, manual examinations are labor extensive and time consuming. In this paper, we conduct a study to analyze the performance of some computer-based lung cancer diagnosis algorithms. The algorithms are built using different feature extraction (gray-level co-occurrence matrix, pixel intensity, histogram and combination of the three) and machine learning (Multi-layer Perceptron and K-Nearest Neighbor) techniques and the performance of each algorithm is compared and analyzed. The result of the study shows that the best performance of lung cancer classification is obtained by the computer algorithm that uses the combined features to characterize lung cancer and subsequently classifies the features using Multi-layer Perceptron

Segmentation of the Electrocardiography Images as a Tool to Identify Heart Diseases

The heart is a very vital organ. Cardiac examination can be done periodically by using an electrocardiograph. So that the heart's condition can be known. One of the optimization in helping the detection of heart disease automatically by using computer assistance. Automatic detection can be done by image processing methods as input, especially ECG images that have been segmented. In this study, ECG image segmentation is carried out through several stages, such as grayscalling, contrast enhancement, and segmentation. The hope, the results of this study can be used as input for automatic detection of heart disease

DETEKSI MANUSIA OTOMATIS PADA GAMBAR CCTV RUANG TERTUTUP SEBAGAI UPAYA PENEGAKAN SOCIAL DISTANCING DI MASA COVID-19

Penelitian ini dilakukan untuk merancang suatu sistem yang mampu melakukan deteksi manusia pada suatu ruangan melalui gambar CCTV secara otomatis. Deteksi tersebut nantinya dapat dijadikan alat penghitung jumlah manusia pada suatu ruangan untuk dilakukan pada era pandemi COVID-19. Hal ini dikarenakan pembatasan jumlah manusia pada suatu ruangan demi menegakkan social distancing merupakan hal yang sangat penting untuk dilakukan demi mencegah penyebaran COVID-19. Sistem  dirancang melalui beberapa tahap, antara lain tahap akusisi data gambar CCTV, pengolahan gambar CCTV, implementasi dan algoritma pendeteksi.Jumlah data gambar CCTV yang akan digunakan adalah sebanyak 2000 sampel. Situs ini menyediakan gambar CCTV yang memuat kerumunan manusia di pusat perbelanjaan. Data yang diperoleh menjadi masukan dari algoritma pendeteksi objek manusia berbasis deep learnig YOLOv3 untuk mendapatkan keluaran berupa hasil deteksi. Berdasarkan hasilnya, sistem dapat dikatakan telah bekerja dengan baik dan memiliki kesempatan untuk diterapkan pada aplikasi yang sebenarnya