Implementasi Gray Level Co-Occurrence Matrix (GLCM) Untuk Klasifikasi Penyakit Daun Padi
نویسندگان
چکیده
Penyakit pada tanaman padi merupakan salah satu faktor yang menyebabkan turunnya tingkat produksi padi. tersebut adalah bacterial leaf blight, smut, brown spot dan sebagainya. Upaya identifikasi sejak dini penyakit dilakukan dengan pemanfaatan algoritma, satunya GLCM klasifikasi KNN. Identifikasi jenis menggunakan metode KNN berdasarkan eksktraksi fitur mengubah citra asli menjadi keabu-abuan (grayscale). Setelah diubah (grayscale), kemudian diekstraksi untuk mendapatkan ekstraksi nilai ciri. Digunakan mengelompokkan kemiripan penyakit. Data digunakan sebanyak 240 gambar diperoleh dari UCI Machine Learning Repository terdiri atas 3 Sebanyak 210 sebagai data training 30 lainnya uji. Hasil penenlitian ini setelah 2 kali proses uji, akurasi tertinggi didapatkan sebesar 93,3%.Kata Kunci: daun padi, klasifikasi, GLCM,
منابع مشابه
Rock Texture Retrieval Using Gray Level Co-occurrence Matrix
Nowadays, as the computational power increases, the role of automatic visual inspection becomes more important. Therefore, also visual quality control has gained in popularity. This paper presents an application of gray level co-occurrence matrix (GLCM) to texturebased similarity evaluation of rock images. Retrieval results were evaluated for two databases, one consisting of the whole images an...
متن کاملTexture Based Image Retrieval Using Framelet Transform–Gral Level Co-Occurrence Matrix(Glcm)
This paper presents a novel content based image retrieval (CBIR) system based on Framelet Transform combined with gray level co-occurrence matrix (GLCM).The proposed method is shift invariant which captured edge information more accurately than conventional transform domain methods as well as able to handle images of arbitrary size. Current system uses texture as a visual content for feature ex...
متن کاملShot boundary detection using second order statistics of gray level co- occurrence matrix
The readily and easily available nature of capturing devices made enormous amounts of video available in day-to-day life. Processing of such a lengthy video is a time consuming process, therefore researchers have introduced key frames. Key frame in short can be visualized as a frame that represents the information present in entire video shot. Detecting shot boundaries plays a vital role in ext...
متن کاملPerformance Analysis of Gray Level Co- Occurrence Matrix Texture Features for Glaucoma Diagnosis
Glaucoma is a multifactorial optic neuropathy disease characterized by elevated Intra Ocular Pressure (IOP). As the visual loss caused by the disease is irreversible, early detection is essential. Fundus images are used as input and it is preprocessed using histogram equalization. First order features from histogram and second order features from Gray Level Co-occurrence Matrix (GLCM) are extra...
متن کاملComputation of gray-level co-occurrence matrix based on CUDA and its optimization
Huichao Hong, Lixin Zheng, Shuwan Pan Engineering Research Center of Industrial Intelligent Technology and Systems of Fujian Providence College of Engineering,Huaqiao University,Quanzhou, China e-mail: [email protected] Abstract: As in various fields like scientific research and industrial application, the computation time optimization is becoming a task that is of increasing importance because of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Jurnal Pseudocode
سال: 2022
ISSN: ['2355-5920', '2655-1845']
DOI: https://doi.org/10.33369/pseudocode.9.1.33-38