Rohana Abdul Karim
Universiti Malaysia Pahang

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Kelulut honey-filled pots detection using image processing based techniques Wan Nur Azhani W. Samsudin; Mohd Harizan Zul; Mohd Zamri Ibrahim; Rohana Abdul Karim
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp1028-1036

Abstract

Kelulut bee is one of the stingless bee species in Malaysia, which is not dangerous to human. Honey from Kelulut bee can be used for the treatment of a variety of illness. The awareness of honey nutrition in our health makes it received high demands from the consumers. Traditionally, beekeepers did the manual inspection to check the honey-filled pots by using the straw or needle. The high demand from the consumers and the greater size of Kelulut beehive make it impractical to check manually all the honeypots which are time-consuming. The hygiene of the collected honey is also important to produce a good quality of honey. Hence, an automated honey-filled pots detection system is proposed to overcome these limitations. The proposed system will reduce the time consuming and less prone to error of the wrong estimation of honey-filled pots. MATLAB software is used to process the image of the Kelulut beehive which is challenging due to the overlapped honeypots in the image. Using the proposed algorithm, it can detect whether the pots filled with honey or not by using image processing techniques and it will analyse the image which represents the percentage amount of honey in the beehives.
Contrast modification for pre-enhancement process in multi-contrast rubeosis iridis images Rohana Abdul Karim; Nurul Wahidah Arshad; Yasmin Abdul Wahab
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 4: August 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i4.22251

Abstract

Existing researchers for rubeosis iridis disease focused on image enhancement as a collective group without considering the multi-contrast of the images. In this paper, the pre-enhancement process was proposed to improve the quality of iris images for rubeosis iridis disease by separating the image into three groups; low, medium and high contrast. Increment, decrement and maintenance of the images’ original contrast were further operated by noise reduction and multi-contrast manipulation to attain the best contrast value in each category for increased compatibility prior subsequent enhancement. As a result, this study proved that there have three rules for the contrast modification method. Firstly, the histogram equalization (HE) filter and increasing the image contrast by 50% will achieve the optimum value for the low contrast category. Experimental revealed that HE filters successfully increase the luminance value before undergoing the contrast modification method. Secondly, reducing the 50% of the image contrast to achieve the optimum value for the high contrast category. Finally, the image contrast was maintained for the middle contrast category to optimise contrast. The mean square error (MSE) and peak signal-to-noise ratio (PSNR) of the outputs were then calculated, yielding an average of 18.25 and 28.87, respectively.