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Showing original image, that is truecolor 24 bit from load image on file store. Showing images converted from the original truecolor 24 bit image. The purpose. Showing the distribution of gray degrees histogram of grayscale image. Performing the calculations of texture characteristics from the parameters mean,. Making decisions, whether the image texture included in ripe or unripe. Analysis of System Requirements. In this study, the software made is expected to be able to recognize the image of.

Table 1. Characteristic Parameters. System Design. Designing Flowchart. The following is a flowchart of image processing application for detecting the. Figure 3. Flowchart of watermelon ripeness detecting application. Designing Form.

Home display of the image processing applications for detecting the lev el of. The main display of the application can be seen on the figure below:. In designing this system, there are major procedures that will be made.

They are:.

Load image. Figure 6. Bmp extension that can be. After choosing the image by selecting the Load. Image , the image files will be displayed in the space provided, as shown below: Figure 7.

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Grayscale Conversion. Figure 8. Display of grayscale image conversion. Histogram of Grayscale Image.

Figure 9. Histogram display of Grayscale Image. The next process is the characteristic of image texture. After the image has been.

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Figure Characteristics Display of Image Texture. In this study, the system testing phase will be performed by processing From these 20 images will be calculated the leve l of. There has been. Watermelon image with bitmap format is converted to grayscale form and the.

Me an, variance, correlation, and entropy is. The calculation of the mean, variance, correlation, and entropy can detect. The result. Table 2. Detection Results of Watermelon Ripeness. N is the total number of the tested watermelon, those ar e 10 ripe watermelons and Tabel 3. Testing Result. Ripe Watermelon. Unripe Watermelon.

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.

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One of the constraints that arise from the use of statistical methods with. H is the lighting. The sampling in the process of collecting data will greatly.

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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. Gambar 3. Histogram dengan 1 "lembah" diantara 2 puncak.

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