WELCOME MESSAGE

My pleasure to welcome all distinguished participants the 2017

International Student Conference on Electrical and Computer

Engineering (ISCECE 2017) which is held on 25th August 2017, in

Wiswacarma Hall, Faculty of Engineering, Udayana University.

The ISCECE 2017 is organized by IEEE Udayana University

Student Branch. The conference is conducted in conjunction with

the 55th Anniversary of Udayana University and the 52nd

Anniversary of Faculty of Engineering

The theme of this conference is “Building Smart Generation

Toward Green Society”. Building smart young generation to create

innovations in order to become green society. The conference has received 10 submissions.

There are 5 papers for presentation but one papers was rejected, so there are 9 papers in this

proceeding.

Thank you to our keynote speaker Prof. Kouichi Takase of Nihon University and our host

speaker Yoga Divayana, Ph.D of Udayana University for their support in this conference. I

would like to thank Department of Electrical Engineering, Faculty of Engineering, Udayana

University for their support and funding. I am gratefully for the all committees of the

International Student Conference on Electrical and Computer Engineering 2017 for their

support to prepare this conference. Finally many thanks for all those participants. Without all

of your supports, the conference couldn’t be held.

I wish you all have a successful conference

Putu Angga Aditya Yoga

ISCECE 2017 Chair

i

ii

ORGANIZING COMMITTEE

Chair :

Putu Angga Aditya Yoga

Co-Chair :

Ni Putu Lintang Anggitiadewi

Secretary :

Ida Bagus Vidananda Agastya

Made Candra Adi Sutra

Finance :

Nia Paramitha

Ida Ayu Sri Sinta Anjani

Program :

Putu Ratih Devyanti

I Wayan Narayana Putra

Mochammad Farhan Arieffadillah

Desak Komang Kharisma Jandinhi

Komang Agus Angga Prasetiawan

Michael Candra Santoso

Wayan Gede Yoga A.W

Joshua Fernaldy Sudarsono

Made Dwi Wiprayoga

Secretariat :

Putu Diana Sari

I Ketut Ary Suarjaya Putra

I Wayan Krisna Saputra

iii

Ni Komang Ayu Sri Anggreni

Gede Teguh Pradnyana Yoga

I Putu Weda Jayanthana

Sponsorship :

Ni Made Anita Belinda

Ni Made Neli Lestari

Agus Satrya Wibawa

I Gede Wiyoga Putra

I Putu Eka April Yanto

I Nyoman Adi Guna Subawa

Anak Agung Gede Agung Semarabawa

I Gede Hery Putrawan

Publication And Documentation :

Komang Triadi Antara

Siti Ayu Oktavianti

Putra Yudhanata Pratama

I Gede Bayu Suarsa

Yoga Kusuma Wardhana

iv

TABLE OF CONTENTS

Welcome Message ......................................................................................................... i

Organizing Committee .................................................................................................... ii

Table of Contents ............................................................................................................ iv

Analyze the Effect of Delay Spread on MIMO Zero Forcing System on Selective Fading

Channel.......................................................................................................................... 1

IG Darma Putra, IGAK Diafari Djuni, NMAED Wirastuti

Field Study at Seloliman Village in East Java using Kali Maron Micro Hydro Power

Plants as Power Supply ................................................................................................. 8

Haksari Laksmi Bestari, I N Satya Kumara

Overview of Integrated Monopole Microcell in Bali.................................................... 15

Rahmat Rudiantono, I Made Indra Wiguna, Linawati

Performance Analysis of Site 3612517G_3G_KUTRI On Football Matches at Dipta

Gianyar Stadium ........................................................................................................... 18

I Made Indra Wiguna, Widyadi Setiawan

Development Of Piezoelectric (Piezoelectric Utilization On The Street To Reducing

Petroleum Usage) .......................................................................................................... 23

Kadek Bintang Anjasmara, I Nyoman Sumitra Tanaya, Nyoman Budiastra,

The Calculation of PSNR Value on Extended Bilateral Motion Estimation and Wavelet

Pyramid Based Multi-Resolution Bilateral Motion Estimation .................................. 27

Muhammad Iman Nur Hakim, N. M. A. E. D. Wirastuti

IoT Based Swimming Pool Stabilizer Using Wemos D1 Mini ..................................... 31

Luh Ayu Sutawati, Made Surya Kumara, Nyoman Wawan Sandi Prayoga, Cok

Gede Indra Partha

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Alternative Energy Sources Using Thermoelectric Modules ...................................... 35

I Made Surya Kumara , Nyoman Wawan Sandi Prayoga , Luh Ayu Sutawati, Gede

Sukadarmika

Designing and Building a Device to Prevent Sexual Crime ......................................... 38

Nyoman Wawan Sandi Prayoga, Ni Kadek Danis Lisyaningsih , Luh Ayu Sutawati,

Marcellino Adi Chrisna Moeri, Ida Bagus Putu Teguh Brahmantika, I Gusti Ngurah

Janardana

Author Index ........................................................................................................................ 45

The Calculation of PSNR Value on Extended

Bilateral Motion Estimation and Wavelet Pyramid

Based Multi-Resolution Bilateral Motion Estimation

Muhammad Iman Nur Hakim1, N. M. A. E. D. Wirastuti2 1,2Postgraduate of Electrical Engineering, Udayana University

Denpasar, Indonesia m.iman.nh@gmail.com

dewi.wirastuti@ee.unud.ac.id

Abstract—The requirement for multimedia information

increase, but the limitations of the network becomes a problem in

the development of multimedia. To overcome this, we need an

image or video processing techniques so that image and video

sent does not require a big sources. One of the techniques is

Extended Bilateral Motion Estimation and Wavelet Pyramid

Based Multi-Resolution Bilateral Motion Estimation that will be

tested on Akiyo video and Container video. The results of this

research are average value of PSNR on Akiyo video with

Extended Bilateral Motion Estimation methods is greater than

the results of Wavelet Pyramid Based Multi-Resolution Bilateral

Motion Estimation method. But in a Container video, Extended

Bilateral Motion Estimation methods produce an average value

lower than Wavelet Pyramid Based Multi-Resolution Bilateral

Motion Estimation methods although indeed differences in value

is not too big either on Akiyo video and Container video.

Keywords—PSNR; Extended Bilateral Motion Estimation;

Wavelet Pyramid Based Multi-Resolution Bilateral Motion

Estimation.

I. INTRODUCTION

With the growing information technology makes images and video delivery request, had to be considered. Moreover, that is currently user are not just looking for information in text form, but rather in the form of pictures and video. However, there are obstacles that must be faced for sending pictures and videos require network resources fairly high, while the channels is quite limited.

With the limitations of the network, it is necessary to do an image processing techniques for the image or video so it can still be sent. However, although has undergone image processing or video processing, image and videos still contain the original information therein and not much different from the original source.

The techniques about image and video processing is a Extended Bilateral Motion Estimation and Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation. This technique is used to reduce the required capacity during transmission and at the decoder, the video will be scaled back to resemble the quality of information sources. Extended Bilateral Motion Estimation is one where motion estimation

compression technique will make the process for determining the movement of an object on a digital video sequences. The movement is generally represented in the form of motion vector at selected points in the current frame compared to other frame is referred as a reference frame [1]. While the concept of wavelet image compression so even though the image data is already compressed (compression) does not eliminate the existing information. Besides being used in a stationary image compression, wavelet is also widely used in several other studies, such as the moving image compression, remote sensing, and detection of computer network activity [2].

II. IMAGE AND VIDEO PROCESSING

A. Extended Bilateral Motion Estimation

Motion Estimation is a process to determine the movement of objects in video sequences. Motion Estimation is one Interframe compression techniques that predict a frame from the previous frame (reference frame), by estimating the movement of blocks between frames. The frame is divided into blocks that do not overlap. Each block is compared to equally sized blocks, on previous frame by block matching

In conducting these match, the location of the most similar block or match on reference frame different from the location of the target block. Differences in the relative positions is called the motion vector (MV), as shown in Fig. 1.

If the position of the target block and the match block are the same, then the motion vector is zero. This motion vector that indicates a shift in the blocks between frames. When encodes each block of a frame that is predictable, vector motion which indicates the position of the block match on reference frame, encoded in the position of the target block itself, then there is compression, because the number of bits needed to encode the vector of motion less than encode a block as a whole.

To improve the accuracy of conventional BME, the extended BME (EBME) [3] extra calculates MV of the block overlapping with each of two adjacent original blocks by half to find the true MV with higher probability than the conventional BME, the dual ME [4] uses the unidirectional and bidirectional matching ratios of blocks in the previous and

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following frames to refine the motion vector field (MVF) of interpolated frame, and the direction-select ME (DS-ME) [5] independently calculates the forward and backward MVs of the interpolated frame and then selects the more reliable one from them by using the sum of bilateral absolute differences (SBAD).

Fig. 1. Motion Vector

B. Wavelet Pyramid Based Multi-Resolution Bilateral Motion

Estimation.

Wavelet transformation is a method for selecting data, function or operator into components of different frequencies, then identify each component at a resolution that matches the scale. The flowchart of Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation illustrated in Fig. 2.

With each of the previous frame ft-1 and following frame ft+1 . Each level of wavelet pyramid consists of two parts: sub sampled image and its edge image, and therefore and edge-dependent term can be included in the block matching criterion to improve the accuracy of Motion Estimation (ME). After the construction of wavelet pyramids, the full-search based BMA is applied to the top-level images (i.e., the images with the lowest resolution) for obtaining the initial MVF of the interpolated frame. [6]. To maintain the same density of MVF at each level, the blocks size of sub sampled decreases by two times. The illustrated of blocks between two pyramids level, it show in Fig. 3.

The bottom-level image (i.e., the input original video frame) is decomposed into four lower resolution components which are respectively called LL sub-band, LH sub-band, HH sub-band and HL sub-band in the clock-wise direction.

The LL sub-band contains the low frequency components of the bottom-level image, and it is extracted from wavelet coefficients to produce the sub-sampled image in the next level. The horizontal, vertical and diagonal directionality of the bottom-level image is clearly presented in the LH, HL and HH sub-bands, and therefore they can be combined into a single edge image by simply zeroing the LL sub-band in wavelet coefficients and then performing the inverse wavelet transform. [6].

Fig. 2. Wavelet Pyramid Based Multi-Resolution Bilateral Motion

Estimation Flowchart

Although the wavelet pyramid multi-resolution search can result in a smoother MVF, the mismatch still exists, which introduces the problem that the mismatch will spread at a lower level when it occurs at a certain level. To alleviate the undesirable effect from the above problem, there add the motion vector smoothing before motion vector refinement at each level to guarantee the reliability of predictive MVs so as to prevent the spread of MV errors.

Fig. 3. Blocks between two pyramid levels.

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III. PSNR VALUES

Peak Signal to Noise Ratio (PSNR) is the ratio between maximum value of the signal measured by the amount of noise that affects the signals. PSNR has a value in decibels (dB). [7] PSNR is used to compare the image quality before and after the image or video processing.

In an image reconstruction, there required comparison between images reconstructed with the original image. Generally used in this case is PSNR. The high of PSNR value states similarity between the results of the reconstruction with the original image.

If obtained PSNR values below 30 dB, it can be stated that the quality is relatively low, where the distortions due to the insertion clearly visible. However, with the value of 40dB or higher, it can be stated that the quality of the output relatively high.

A. PSNR Value with EBME.

In this research, used Akiyo video and Container video with cif quality. Differences between these videos are on the subject of motion in the video. Container video contains more motion than Akiyo video. From the experimental results, obtained each PSNR in Fig. 4 for EBME with Akiyo video, Fig. 5 for EBME with Container video, Fig. 6 for Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation with Akiyo video, and Fig. 7 for Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation with Container video.

In the research using EBME, on Akiyo video obtained the highest PSNR value at 51.36611 dB and the lowest at 40.86623 PSNR dB. In Fig. 4 is shown PSNR on each frame.

Fig. 4. PSNR with EBME on Akiyo video.

In Fig. 5 is shown PSNR value each frame of Container video. The maximum PSNR values obtained in this research at 45.70234 dB and a minimum value at 43.84589 dB PSNR. The average PSNR with EBME on the both are 46.67279 dB for Akiyo video and 44.92818 dB for Container video.

Fig. 5. PSNR with EBME on Container video.

B. PSNR Value with Wavelet Pyramid Based Multi-

Resolution Bilateral Motion Estimation

Using the Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation method on Akiyo video, the highest PSNR value is 51.36611 dB and the lowest PSNR value is 41.18155 dB. Each PSNR value from every frame can be seen in Fig. 6. It is not too much different between the result in Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation and EBME.

Fig. 6. PSNR with Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation on Akiyo video.

In the Container video, the highest PSNR value is 45.72245 dB and the lowest PSNR value is 43.856 dB. In Fig. 7 shown PSNR value in each frame. From the resulting of graph, looks not much different from previous results on EBME method. This is close with the result of the Akiyo video. In the research of Wavelet Pyramid Based Multi-Resolution Bilateral Motion

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Estimation obtained PSNR average value for Akiyo video at 46.66738 dB and 44.94364 dB for Container video.

Fig. 7. PSNR with Wavelet Pyramid Based Multi-Resolution Bilateral

Motion Estimation in Container video.

The results of PSNR values have been obtained, we can show in the form of a table as shown in Table 1. The highest PSNR value in video Akiyo have similarities in both methods. Neither the method nor the Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation. The highest PSNR value at 51.36611 dB.

TABLE I. PSNR VALUES

PSNR Akiyo Container

EBME Wavelet

Pyramid EBME

Wavelet

Pyramid

Highest PSNR 51.36611

dB

51.36611

dB

45.70234

dB

45.72245

dB

Lowest PSNR 40.86623

dB 41.18155

dB 43.84589

dB 43.856 dB

Average PSNR 46.67279

dB

46.66738

dB

44.92818

dB

44.94364

dB

IV. CONCLUSION

From the result of research the largest PSNR average value of two methods featured in the Akiyo video than Container video. The average PSNR of both methods on Akiyo video is 46.6 dB, while on video Container is 44.9 dB. However, the average value of Container video, which contains more

movement of the subject, produced greater by Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation method than EBME method. Although the difference in value is not too significant. Similarly, the highest nor the lowest PSNR, resulting in greater in Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation than EBME even though the value is small. Overall, the Akiyo video obtained better results with EBME method, whereas in the Container video obtained better results by using Wavelet Pyramid Based Multi-Resolution Bilateral Motion Estimation.

REFERENCES

[1] P.E. Priyatna Panja, “Penggunaan motion estimation untuk perbaikan gerakan objek pada kompresi video” [The use of motion estimation for repair object on the movement of video compression], 2011.

[2] Tb. Ai, Munandar, M. Adelvin L., Alb. Joko Santoso, “Analisa PSNR, rasio kompresi warna dan MSE terhadap kompresi image menggunakan 31 fungsi wavelet.” [Analysis of PSNR, color compression ratio and MSE against image compression using 31wavelet function], Atma Jaya University, Yogyakarta. March, 2014.

[3] S.-J.Kang, K.-R.Cho, and Y.H.Kim, “Motion compensated frame rate up-conversion using extended bilateral motion estimation,” IEEE Trans. Consum. Electron., vol.53, no.4, pp.1759–1767, 2007. On R. Li, H. Liu, J. Chen, and Z. Gan, “Wavelet pyramid based multi-resolution bilateral motion estimation for frame rate up-conversion,” no. 1, pp. 208–218, 2016.

[4] S.-J.Kang, S.Yoo, and Y.H.Kim, “Dual motion estimation for frame rate up-conversion,” IEEE Trans. Circuits Syst. Video Technol., vol.20, no.12 ,pp.1909–1914, 2010. On R. Li, H. Liu, J. Chen, and Z. Gan, “Wavelet pyramid based multi-resolution bilateral motion estimation for frame rate up-conversion,” no. 1, pp. 208–218, 2016.

[5] D.-G.Yoo, S.-J.Kang, and Y.H.Kim, “Direction-select motion estimation for motion-compensated frame rate up-conversion,”J. Display Technol., vol.9, no.10, pp.840–850, 2013. On R. Li, H. Liu, J. Chen, and Z. Gan, “Wavelet pyramid based multi-resolution bilateral motion estimation for frame rate up-conversion,” no. 1, pp. 208–218, 2016.

[6] R. Li, H. Liu, J. Chen, and Z. Gan, “Wavelet pyramid based multi-resolution bilateral motion estimation for frame rate up-conversion,” no. 1, pp. 208–218, 2016.

[7] G.M. Male, Wirawan, E. Setijadi, “Analisa kualitas citra pada steganografi e-government” [Analysis of image quality on e-government steganography], Proceedings of 15th the National Seminar on Management of Technology, pp. 1–9, 2012.

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AUTHOR INDEX

A

Anjasmara, Kadek Bintang ...................................... 23

B

Bestari, Haksari Laksmi ........................................... 8 Budiastra, Nyoman .................................................. 23

Brahmantika, Ida Bagus Putu Teguh ........................ 38

D

Darma Putra, IG ...................................................... 1

Diafari Djuni, IGAK ............................................... 1

H

Hakim, Muhammad Iman Nur ................................... 27

J

Janardana, I Gusti Ngurah......................................... 38

K

Kumara, I Made Surya ........................................... 31, 35

Kumara, I N Satya ................................................. 8

L Linawati ................................................................. 15

Lisyaningsih, Ni Kadek Danis ................................ 38

M

Moeri, Marcellino Adi Chrisna ........................................ 38

P

Prayoga, Nyoman Wawan Sandi ............................. 31, 35, 38

Partha, Cok Gede Indra ...................................................... 31

R

Rudiantono, Rahmat ………………........................ 15

S

Setiawan, Widyadi ………………......................... 18

Sukadarmika, Gede ………………....................... 35

Sutawati, Luh Ayu ………………......................... 31, 35, 38

T

Tanaya, I Nyoman Sumitra ………......................... 23

W

Wiguna, I Made Indra ………….…........................ 15, 18 Wirastuti, NMAED ................................................. 1

Wirastuti, N.M.A.E.D ............................................. 27