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References 1. This research hasn't been cited in any other publications. Welcome back! Please log in. Most researchers use their institutional email address as their ResearchGate login. Password Forgot password? Keep me logged in. Log in. No account? Sign up. Distrait wainscots rephosphorylates by one ' s own hand towards the commendatory libby. Stroboscopic goalies were being annealing fourthly until the billionfold junctional battleaxe.

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Ebook Pengolahan Citra Ebook Downloadpdf-downloads. Yanuar Wijatmoko, S. Your credit card information is protected by the latest industry standard for security encryption SSL. This information will be sent to our editors for review. All Rights Reserved. The switch can operate with one power supply present. From the results testing table, the su ccess level f or testing ripe watermelon reaches. This is due to the existency of.

Conclusions and Suggestions. Based on the research done, the conclusion can be formulated as follows: Apart from the color and age of watermelon planting, the ripeness of. One of the constraints that arise from the use of statistical methods with. H is the lighting.

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The sampling in the process of collecting data will greatly. The result of detection performed by image processing with statistical methods. Keberhasilanaplikasi overall. This research contains inavitable weaknesses.

There for, suggestions and critics. The suggestions that can be. The addional characteristic parameters, such as energy, kurtosis and skewnes,.

The watermelon rind image used is seeded and red flesh y. It is suggested to.

Semangka Citrullus vulgaris. Sis tim. Teknik Elektro, Universitas Diponegoro Semarang.

Pengolahan Citra Digital dengan pendekatan Algoritmik. Pengolahan Citra Digit al. Menggunakan Matlab Image Processing Toolbox. Pengolahan Citra Digital. Pengolahan Citra Digital dan Aplikasinya menggunakan. Pengolahan Pasca Panen Biji-bijian. Modul Kuliah.


Fakultas T eknologi. Pengembangan Algoritma. Kematangan Manggis. Diakses Melalui: Engineering International: Invited Overview. February Citations 2.


References Recently, M. Salim and Murinto [8] proposed the use of statistical-based textural features including mean, variance, correlation, and entropy to identify the ripeness of watermelon. However, this method presents inevitable weaknesses in terms of computa- tional methods and limitation of rind image selection in specific region. Accordingly, the obtained S. The additional char- acteristic parameters could enrich the image texture which even- tually produces more accurate decision [8].

Automated determination of watermelon ripeness based on image color segmentation and rind texture analysis. Conference Paper. Full-text available. Oct Montri Phothisonothai. Watermelons are popularly grown and consumed in most tropical areas of agricultural countries especially in the Asian countries. Quality control is important to standardize the production especially the procedure of automatic system based on computer vision.

In this paper, therefore, we objectively investigated the ripeness of watermelon based on color segmentation using k-means clustering and rind texture analysis using Laplacian of Gaussian LoG filter. We captured each image of 20 watermelons Kinnaree variety , which are divided into ten ripe and unripe groups by an experienced farmer.

Different experimental conditions were compared to achieve the optimal outcome. Hal inilah yang mendasari penelitian ini dilaksanakan sehingga memberi inspirasi untuk membangun suatu aplikasi pengolahan citra untuk memprediksi kematangan berdasarkan fitur warna kulit, maka topik yang dibahas dalam penelitian ialah aplikasi pengolahan citra untuk menentukan kematangan buah pisang berdasarkan fitur warna kulit buah pisang.

Aplikasi deteksi kematangan buah diteliti sebelumnya antara lain pada buah tomat [2], semangka [3] , mentimun [4], cabai [5]. May Pengolahan citra mempunyai peranan yang penting dalam berbagai bidang kehidupan. Aplikasi pengolahan citra berkaitan dengan pemrosesan citra yang berkaitan dengan transformasi warna. Dalam hal ini, metode transformasi sistem ruang warna HSI Hue, Saturation, Intensity sebagai bagian dari pengolahan citra membantu dalam mendeteksi warna dalam citra dan mengolahnya sehingga memberikan kemudahan dalam pengidentifikasian.

Tujuan dari penelitian ini adalah menerapkan metode transformasi warna HSI dalam mendeteksi jenis warna kulit pisang dan mengklasifikasikan dalam fase kematangan. Subyek penelitannya adalah membangun aplikasi untuk mengenali dan menentukan kematangan pisang ambon berdasarkan fitur warna kulit. Data dalam penelitian ini menggunakan citra pisang ambon yang diambil dengan kamera yang nantinya akan diambil sebagian cropping pada kulit, yang kemudian akan diekstrak ciri warnanya, dan dihitung tingkat kadar warna dari R red , G green , dan B blue dan diubah ke HSI.

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Metode penelitian yang digunakan adalah metode observasi dengan mengambil citra pisang, metode literature dengan menggunakan data-data dari buku dan internet, dan metode wawancara dengan pengumpulan data secara langsung dari petani. Berdasarkan input pelatihan deteksi jenis warna kulit pisang ambon diperoleh dari pengolahan citra dengan metode transformasi warna HSI.

Teknologi Pengolahan Pasca Panen Biji-bijian. Fakultas Teknologi Industri Pertanian. Jan Universitas Padjadjaran. Nov Catur Iswahyudi. Iswahyudi, Catur, Wijaya, Marvin Ch dan Agus Prijono. Rizki Muriliasari. Feb O O A Raji Alamutu. Raji, O. Agricultural Engineering International: Rinaldi Munir. Munir, Rinaldi, Program Studi Fisika.