Volume1 Issue12019-03-10T20:17:31+00:00

Volume 1: Issue 1

Volume 1: Issue 1

A note from the Editor in Chief

Every new day comes with a new hope, and so it seems appropriate to start our first issue with a brief letter to announce the establishment of Artificial Intelligence Innovations Journal. We have launched this journal as a nonprofit open-access platform to create a fast and convenient opportunity of publication, for any noteworthy research in the field of artificial intelligence. Our main goal is to provide students, researchers, and academicians with a free and high-quality publication service, so as to promote their latest findings, and to stimulate research in the field of artificial intelligence, by supporting and funding their bright ideas.

Moreover, we strive to ease international scientific communications in the field of artificial intelligence, by gathering cutting-edge scientific findings in most sub-fields of mathematics and creating a quality environment for researchers, to exchange their knowledge.

Automated Detection of Flaws in Apple Fruits

Author(s):  Abdulkader Helwan, Mohammad khaleel Sallam Ma’aitah
Keywords:  Flaws Detection, Ripeness, Segmentation, Edges, Filtering, Image Fusion
Refer this article:  A. Helwan, M. KS. Ma’aitah, Automated Detection of Flaws In Apple Fruits, Artificial Intelligence Innovations Journal. 1 (1) (2019) 4-13.

Image processing techniques have been used in fruit industry extensively. This shows great results in fruit sorting, classification, ripeness detection, and flaws detection and segmentation. Combining different image processing methods such as filtering, enhancement, and edge detection can provide good and promising results in fruit flaws segmentation. In this work, we attempt to detect the flaws in apple fruits by creating an algorithm based on image processing. This algorithm is a bunch of image processing techniques such median filtering, followed by image enhancement to remove noise from images and to increase their pixel intensities. Moreover, edge detection is used for finding edges of the flaws found in apple images. Image fusion is then used in order to contour the flaws found in apples by putting the segmented and original image on each other’s. Finally, the system was tested on many images and it showed a good performance in finding and contouring the flaws in apple fruit images.
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