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حل اسئلة وسائط متعددة قسم الحاسوب الجامعة المستنصرية نموذج رقم1

حل اسئلة وسائط متعددة قسم الحاسوب الجامعة المستنصرية نموذج رقم1

حل اسئلة وسائط متعددة قسم الحاسوب الجامعة المستنصرية نموذج رقم1

Question #1/ Choose the correct answer (answer 15 only)

(1) In video camera, the light is converted into electronic signals by a special sensor called
(A) ADC (B) DAC (C) CCD (D) both A and B

(2) In digitized sound, the sampling rate must be at least ______ the highest frequency in the signal.
(A) equal  (B) Twice (C) half  (D) 1.5 time

(3) Image _____ is used to extract useful information from images.
(A) sampling  (B) quantization  (C) Filter  (D) logic operation

4) In Nyquist Theorem the sampling rate Should be _____ .
(A)(f1-f2)/2  (B) (2f2-f1)  (C) 2(f2-f1)  (D) 2(f2/f1)

5) ____ color models used in applications in computers, smartphones, TVs, and cameras.
(A) CMYK  (B)RGB  (C) HSV  (D) Both A and B

(6) In multimedia, a graph is a collection of _____ .
(A) vertices  (B) edges  (C) curves  (D) A and B

(7) Games show is an example of ____ multimedia.
(A) Linear  (B) continuous  (C) non linear  (D) discrete

(8) In terms of computing, ______  are fundamental multimedia attributes:
(A) Digitized  (B) distributed  (C) Interactive  D)All the above

(9) ____ image format which most important current standard for image compression.
A)JPEG   (B) TIIF   (C) PNG  (D) GIF

(10) 2 MB file is compressed using JPEG compression, the file will be reduced into _____
(A) 50 KB   (B) 100 KB   (C) 20 KB  (D) 25 KB

(11) the ____ video format is a common format on the Internet, but movies cannot be played on a
Windows computer without an extra (free) component installed.
(A) MPEG   B) Quick time   (C) WindowMedia   (D) RealVideo

(12) _____ takes a lot of storage space.
(A) Graphic Images   (B) Audio   (C) Video   (D) Animation

(13) _____ is an example of animation technique.
(A) Traditional animation    (B) Computer animation
(C) 2D and 3D animation    (D) Key-Frame

(14) The text elements used in multimedia in _____ fields
(A) Symbol and icons    (B) Interactive buttons
(C) HTML documents   (D) All the above

(15) In multimedia text _____ used to modify the size, style, and color of font to convey meaning.
(A) Font properties    (B) align and space
(C) warp text             (D) Spatial formatting and effects

(16) The_____ text elements used in multimedia to help the user navigates through the content.
(A) Menus    (B) Interactive buttons   (C) HTML documents    (D) Web sites

(17) _____ is simplest type of images with two ----- values contain brightness, no color information
(A) Binary, Gray scale   (B) Gray scale, Binary   (C) Gray scale, color    (D) Binary, color

(18) Computer vision systems are used in many and various types of environments, one of the
following is not included
 (A) Medical Community (B) Mobile IP Systems (C) Satellites Orbiting (D) DNA analysis

(19) In animation , once rendered, final images are :
(A) Saved in Database   (B) Filtered form noise  (C) added audio files  (D)transferred to film

(20) In typical image the noise can be modeled with many models of distribution, one of the
following is not included
(A) Random distribution model of noise    (B) Gaussian ("normal") distribution.
(C) Uniform distribution.   (D) Salt _and _pepper distribution.

(21) Histogram Equalization Is a popular technique used :
(A) for remove all noise from images    (B) for improving the appcarance of a poor image
(C) for segmenting the selected images   (D) for repair the damaged images and returned it to its original aspect.

(22) The amount of data a communication channel can carry is :
(A) RGB channel   (B) LAN network   (C )Database size   (D) Bandwidth

QUESTION #2/ Define the following: (answer five only) [10 Marks]

(1) Authoring Tools               (2) Image-compression
(3) High pass filter                (4)3D animation
(5) Nequist theorem              (6) Compression Ratio
(7) Color models                   (8) Morphing
(9) Color depth in images
(10) Signal to Noise Ratio (SNR)


1) Authoring Tools: These are software applications used to create multimedia content. They allow users to combine various forms of media such as text, graphics, audio, and video into an integrated presentation.

1) أدوات التأليف: هذه هي التطبيقات البرمجية المستخدمة لإنشاء محتوى الوسائط المتعددة. إنها تسمح للمستخدمين بدمج أشكال مختلفة من الوسائط مثل النصوص والرسومات والصوت والفيديو في عرض تقديمي متكامل.

2) Image Compression: This is the process of reducing the size of a digital image file without significantly affecting its visual quality. It is typically achieved by removing redundant or unnecessary information from the image.

2) ضغط الصور: هذه هي عملية تقليل حجم ملف الصورة الرقمية دون التأثير بشكل كبير على جودتها المرئية. يتم تحقيق ذلك عادةً عن طريق إزالة المعلومات الزائدة أو غير الضرورية من الصورة.

3) High Pass Filter: A type of filter used in signal processing to pass signals with frequencies higher than a certain cutoff frequency while attenuating signals with frequencies lower than the cutoff frequency. It is often used to enhance or sharpen images by emphasizing high-frequency components.

3) مرشح التمرير العالي: نوع من المرشحات يستخدم في معالجة الإشارات لتمرير الإشارات بترددات أعلى من تردد قطع معين مع توهين الإشارات بترددات أقل من تردد القطع. غالبًا ما يتم استخدامه لتحسين الصور أو زيادة وضوحها من خلال التركيز على المكونات عالية التردد.

4) 3D Animation: Animation that involves the creation of three-dimensional moving images. It is typically produced using computer software and involves the manipulation of 3D models to create the illusion of motion.

4) الرسوم المتحركة ثلاثية الأبعاد: الرسوم المتحركة التي تتضمن إنشاء صور متحركة ثلاثية الأبعاد. يتم إنتاجه عادةً باستخدام برامج الكمبيوتر ويتضمن معالجة النماذج ثلاثية الأبعاد لإنشاء وهم الحركة.

5) Nyquist Theorem: Also known as the Nyquist-Shannon sampling theorem, it states that in order to accurately reconstruct a continuous signal from its samples, the sampling frequency must be at least twice the highest frequency present in the signal.

5) نظرية نيكويست: المعروفة أيضًا باسم نظرية نيكويست-شانون لأخذ العينات، تنص على أنه من أجل إعادة بناء إشارة مستمرة بدقة من عيناتها، يجب أن يكون تردد أخذ العينات على الأقل ضعف أعلى تردد موجود في الإشارة.

6) Compression Ratio: In the context of data compression, the compression ratio is the ratio of the size of the uncompressed data to the size of the compressed data. It indicates how much the data has been reduced in size through compression.

6) نسبة الضغط: في سياق ضغط البيانات، نسبة الضغط هي نسبة حجم البيانات غير المضغوطة إلى حجم البيانات المضغوطة. يشير إلى مقدار البيانات التي تم تقليل حجمها من خلال الضغط.

7) Color Models: These are mathematical models that describe the way colors can be represented as tuples of numbers. Common color models include RGB (Red, Green, Blue), CMYK (Cyan, Magenta, Yellow, Black), and HSV (Hue, Saturation, Value).

7) نماذج الألوان: هذه نماذج رياضية تصف الطريقة التي يمكن بها تمثيل الألوان كمجموعات من الأرقام. تتضمن نماذج الألوان الشائعة RGB (الأحمر والأخضر والأزرق) وCMYK (السماوي والأرجواني والأصفر والأسود) وHSV (تدرج اللون والتشبع والقيمة).

8) Morphing: A special effect in animation where one image gradually transforms into another. This is achieved by creating a series of intermediate frames that smoothly transition between the two original images.

8) التحويل: تأثير خاص في الرسوم المتحركة حيث تتحول صورة تدريجياً إلى أخرى. يتم تحقيق ذلك من خلال إنشاء سلسلة من الإطارات الوسيطة التي تنتقل بسلاسة بين الصورتين الأصليتين.

9) Color Depth in Images: Also known as bit depth, color depth refers to the number of bits used to represent the color of each pixel in an image. It determines the range of colors that can be displayed in the image, with higher color depths allowing for more colors and smoother gradients.

9) عمق اللون في الصور: يُعرف أيضًا باسم عمق البت، ويشير عمق اللون إلى عدد البتات المستخدمة لتمثيل لون كل بكسل في الصورة. فهو يحدد نطاق الألوان التي يمكن عرضها في الصورة، مع أعماق ألوان أعلى تسمح بمزيد من الألوان وتدرجات أكثر سلاسة.

10) Signal-to-Noise Ratio (SNR): A measure used to quantify the ratio of the strength of a signal to the amount of noise present in the signal. It is often expressed in decibels (dB) and is used to assess the quality of a signal, with higher SNR values indicating better signal quality.

10) نسبة الإشارة إلى الضوضاء (SNR): مقياس يستخدم لقياس نسبة قوة الإشارة إلى مقدار الضوضاء الموجودة في الإشارة. يتم التعبير عنه غالبًا بالديسيبل (dB) ويستخدم لتقييم جودة الإشارة، حيث تشير قيم SNR الأعلى إلى جودة إشارة أفضل.

Question #3/ Answer A or B

#A Choose True or False and correct if false (Answer five)

(1) Fill light reduces shadows, separates the subject from the background.
(2) The procedure for conversion the analog video to digital format involves two
types of devices- source devices and capture devices.
(3)For audio, typical sampling rates are 16 kHz.
(4) Image crop process is done by reducing the amount of data that need to be
(5)Color image can be modeled as three band monochrome image data, where each
band of the data corresponds to a different color.
(6) Images produced from optical scanners and digital cameras are vector graphics.
(7) Linear text represented in a semantic hetwork in which multiple related sections
of the text are connected to each other.


1) True. 

2) True. 

3) False. Typical sampling rates for audio can vary, but common rates include 44.1 kHz (CD quality), 48 kHz (DVD quality), and higher for professional audio.

4) True. 

5) False. A color image is typically represented as three separate channels for red, green, and blue (RGB), rather than three bands of monochrome image data.

6) False. Images produced from optical scanners and digital cameras are typically raster graphics, not vector graphics. Vector graphics are generated by mathematical equations and are resolution-independent.

7) False. Linear text is typically represented in a sequential format, such as plain text or formatted text files. Semantic networks are used to represent relationships between concepts, not linear text.

#B Consider the below imago (Answer two only)

 7  1  4 
 3   6  0
 1  0   2

1- Draw the Histogram, then apply Histogram Modifications of shrink for ( {Image (1,0)} only select shrink max 6 & shrink min 1).


  1. Histogram: To draw the histogram, we count the frequency of each pixel intensity level in the image.

    Pixel Intensity LevelFrequency

    The histogram visually represents the distribution of pixel intensities in the image.

  2. Histogram Modification - Shrink for {Image (1,0)} with shrink max 6 & shrink min 1: Shrink is a histogram modification technique that adjusts the intensity levels of an image. The shrink operation compresses the intensity levels, mapping a wider range of intensities to a narrower range.

    Here, we're focusing on the pixel value at position (1,0), which is 1.

    Shrink Min: 1 Shrink Max: 6

    The formula for shrink is: NewIntensity = ((OldIntensity - Min) / (Max - Min)) * NewMax

    For the pixel at (1,0), the old intensity is 1, the minimum intensity is 1, the maximum intensity is 6, and the new maximum is 255 (assuming 8-bit grayscale).

    NewIntensity = ((1 - 1) / (6 - 1)) * 255 = (0 / 5) * 255 = 0 * 255 = 0

    So, the new intensity for pixel (1,0) after shrink operation is 0.

2- Apply Mean filter for Image Pixel (1,1)=6 and explain for what purpose Mean filter is used?


The neighborhood consists of the pixels with intensity values: 7, 1, 4, 3, 6, 0, 1, 0, 2.

To calculate the mean (average) intensity value of this neighborhood:

Mean = (7 + 1 + 4 + 3 + 6 + 0 + 1 + 0 + 2) / 9 = 24 / 9 ≈ 2.67

So, we would replace the intensity value of the pixel at (1,1) with the rounded mean value, which is approximately 3.

The modified image would look like this:

7 1 4
3 3 0 
1 0 2

3) Resize the above image using Zero-Order-Hold.


Let's say we want to resize it to a 5x5 image using ZOH. We'll duplicate each pixel horizontally and vertically:

7 7 1 1 4 
 7 7 1 1 4 
 3 3 6 6 0
 3 3 6 6 0 
 1 1 0 0 2

QUESTION #4/ Answer the following: (answer two only)

(1) Enlarge an image to 6 times, for two adjacent pixel values 0 and 12.


1. 12-0 = 12 ( differences of color value between the two adjacent pixels) 
2. K = 6 ----> 12/6 = 2
3. K-1 = 6-1 = 5
4. K = 1 -> 0 + 2*1 = 2
5. K = 2 -> 0 + 2*2 = 4
6. K=3 -> 0 + 2*3 = 6
7. K= 4 -> 0 + 2* 4 = 8
8. K= 5 -> 0 + 2* 5 = 10

(2) Calculate the storage memory required to store two-minute video if the still image require two megabyte of storage memory and the number of still images required is 30 to provide the appearance in one second?


Number of still images for two minutes = 30 images/second * 60 seconds/minute * 2 minutes = 3600 images

Total storage memory required = 3600 images * 2 megabytes/image = 7200 megabytes

Therefore, the storage memory required to store a two-minute video is 7200 megabytes.

(3)For 100x100 color image, Calculate the number of gray or color levels and the storage size in KB?


Storage size in bytes = image width * image height * color depth

Storage size = 100 * 100 * (8 bits/channel * 3 channels) = 100 * 100 * 24 bits

Storage size in kilobytes (KB) = (Storage size in bytes) / 1024

Therefore, the image has 16,777,216 color levels, and the storage size is approximately 234.375 KB.

(4) Consider the below table of an image and its properties Use Shannon-Fano Coding to find total number of bits with diagram

Symbol     A    B    C   D    E

Count       14   9     8    7     5


1. Sort Symbols by Frequency:

As you already pointed out, the first step is to sort the symbols by their frequency (count) in descending order:


2. Build the Shannon-Fano Tree:

  1. Start by combining the two symbols with the lowest frequencies. In this case, combine D (7) and E (5) to form a temporary node with a total count of 12.
  2. Now, we have four nodes: A (14), B (9), C (8), and the temporary node (D+E) (12).
  3. Combine the two nodes with the next lowest total counts. Since both B (9) and the temporary node (D+E) (12) have similar counts, we can choose either one arbitrarily. Here, let's combine B (9) and the temporary node (D+E) (12) to form another temporary node with a total count of 21.
  4. We are now left with three nodes: A (14) and the two temporary nodes (B+D+E) (21) and C (8).
  5. Finally, combine the remaining two nodes. Here, combine A (14) and the temporary node (B+D+E) (21) to form the root node with a total count of 35.

Shannon-Fano Tree Diagram:

          /   \
       (21)    (14)
        /   \    
      (12)    (9)
       /   \
      (7)   (5)
       D     E

3. Assign Codewords:

  1. Traverse the tree starting from the root. Assign a 0 (zero) to the left branch and a 1 (one) to the right branch at each level.
  2. For each symbol, follow the path from the root to its leaf node in the tree. The codeword for the symbol is the sequence of 0s and 1s encountered during this path.

Here's the table with assigned codewords:


4. Calculate Total Number of Bits:

  1. Multiply the frequency (count) of each symbol by the length of its codeword in bits.
  2. Sum the products for all symbols.
SymbolCountCodeword LengthProduct (Count * Length)

Total Bits = 14 + 18 + 16 + 21 + 15 = 84 bits

(5) Compare between the following briefly (answer Two only)

Interactive Multimedia                  VS               Hyper Media           

Subtraction of two images           VS               Multiplication of two images

Image restoration                          VS               image enhancement

Laplace filter                                  VS               Median filter


FeatureInteractive MultimediaHypermedia
User interactionHigh, users can control content flowLow, users navigate through predefined links
ExamplesGames, simulations, e-learningEducational websites, online encyclopedias

FeatureSubtraction of Two ImagesMultiplication of Two Images
OperationSubtracts corresponding pixel valuesMultiplies corresponding pixel values
ResultHighlights differences between imagesCreates a brighter or darker image depending on pixel values
ApplicationsBackground subtraction, motion detectionNight vision enhancement, artistic effects

FeatureImage RestorationImage Enhancement
GoalRecover lost or corrupted image dataImprove the visual quality of an image
ExamplesRemoving noise, scratches, blurringAdjusting contrast, brightness, sharpening
ApplicationsRestoring historical photographs, medical imagingCreating visually appealing images for websites, presentations

FeatureLaplace FilterMedian Filter
OperationDetects edges and high-frequency detailsRemoves noise while preserving edges
ApplicationsEdge detection, object recognitionDenoising images, removing salt-and-pepper noise

QUESTION #5/ Explain the following: (answer five only)

(1)Post-production stage in multimedia project.
(2) Draw simple diagram represents Compression System Model-
(3) Quantization of Audio.
(4) Keyframe-based animation.
(5) Advantage of digital video.
(6) The advantage of using multimedia.
(7) Data reduction in image analysis.
(8) What is mean by rendering? What is the next step after rendering in producing 3D movies? Explain briefly.


Explanations for Multimedia Concepts:

(1) Post-production stage in a multimedia project:

This is the stage after the raw materials (video, audio, images, text) have been captured or created. It involves editing, processing, and combining all the elements to create the final multimedia product. Key tasks include:

  • Editing: Assembling and arranging the captured footage, audio tracks, and other elements in a logical sequence.
  • Adding effects: Applying transitions, filters, and special effects to enhance visual appeal.
  • Color correction: Adjusting color balance, contrast, and brightness for better image quality.
  • Audio mixing: Balancing audio levels, adding background music or sound effects, and incorporating narration.
  • Encoding: Converting the final product into a specific format suitable for delivery (e.g., MP4, AVI).

(2) Compression System Model Diagram:

Here's a simple diagram representing a compression system model:

          +------------+      +------------+
          |  Source   | ------> | Encoder   | ------> Compressed Data
          +------------+      +------------+           (compressed format)
          +------------+      +------------+
          |  Decoder   | ------> |  Sink     |
          +------------+      +------------+
          +------------+      +------------+
          | Destination| ------> | (Final Output)
          +------------+      +------------+
  • Source: The original uncompressed data (e.g., audio, video, image).
  • Encoder: Analyzes the data and applies compression techniques to reduce its size.
  • Compressed Data: The data in a smaller format after applying compression.
  • Decoder: Receives the compressed data and decompresses it back to a usable format.
  • Sink: The device or application that receives the final output (e.g., computer screen, speakers).
  • Destination: The final form in which the data is presented (e.g., video displayed on a screen, audio played through speakers).

(3) Quantization of Audio:

This is a lossy compression technique used in audio encoding. It reduces the number of bits needed to represent an audio signal by grouping similar amplitude values into discrete levels (quantization bins). While this reduces the file size, it can introduce some loss of audio fidelity.

3) تكميم الصوت:

هذه تقنية ضغط مع فقدان البيانات تستخدم في تشفير الصوت. فهو يقلل من عدد البتات اللازمة لتمثيل إشارة صوتية عن طريق تجميع قيم السعة المماثلة في مستويات منفصلة (صناديق التكميم). على الرغم من أن هذا يقلل من حجم الملف، إلا أنه قد يؤدي إلى فقدان بعض الدقة في الصوت.

4) Keyframe-based animation:

This is a widely used animation technique where only the key poses or positions of an object are defined at specific points in time (keyframes). The software automatically interpolates (calculates) the in-between frames to create a smooth animation sequence. This approach simplifies the animation process and reduces file size compared to storing every single frame.

4) الرسوم المتحركة المستندة إلى الإطار الرئيسي:

هذه تقنية رسوم متحركة مستخدمة على نطاق واسع حيث يتم تحديد أوضاع أو مواضع المفتاح فقط للكائن في نقاط زمنية محددة (الإطارات الرئيسية). يقوم البرنامج تلقائيًا بإقحام (حساب) الإطارات البينية لإنشاء تسلسل رسوم متحركة سلس. يعمل هذا الأسلوب على تبسيط عملية الرسوم المتحركة وتقليل حجم الملف مقارنة بتخزين كل إطار على حدة.

(5) Advantages of digital video:

  • Easy editing and manipulation: Digital video can be easily edited, trimmed, and combined using software tools.
  • High quality and fidelity: Digital video offers superior image quality compared to analog formats, with less degradation over time.
  • Copying and distribution: Digital video can be easily copied and distributed without loss of quality.
  • Special effects and compositing: Digital video allows for advanced special effects and compositing techniques, creating visually stunning outcomes.
  • Storage and accessibility: Digital video can be stored efficiently on hard drives or streamed online, making it readily accessible.
5) مزايا الفيديو الرقمي:
سهولة التحرير والمعالجة: يمكن تحرير الفيديو الرقمي وقصه ودمجه بسهولة باستخدام الأدوات البرمجية.
جودة ودقة عالية: يوفر الفيديو الرقمي جودة صورة فائقة مقارنة بالتنسيقات التناظرية، مع تدهور أقل بمرور الوقت.
النسخ والتوزيع: يمكن نسخ الفيديو الرقمي وتوزيعه بسهولة دون فقدان الجودة.
المؤثرات الخاصة والتركيب: يتيح الفيديو الرقمي استخدام المؤثرات الخاصة وتقنيات التركيب المتقدمة، مما يؤدي إلى نتائج مذهلة بصريًا.
التخزين وإمكانية الوصول: يمكن تخزين الفيديو الرقمي بكفاءة على محركات الأقراص الثابتة أو بثه عبر الإنترنت، مما يسهل الوصول إليه.

6) Advantages of using multimedia:

  • Engages multiple senses: Multimedia presentations can engage viewers through sight, sound, and possibly even touch or interactivity, enhancing learning and retention.
  • Information clarity and presentation: Multimedia elements (images, videos, audio) can help simplify complex information, making it easier to understand and remember.
  • Increased user interaction: Interactive multimedia allows users to explore information at their own pace and control the flow of the presentation, promoting active learning.
  • Appeal to different learning styles: Multimedia caters to different learning styles (visual, auditory, kinesthetic) by presenting information in multiple ways.
  • More engaging and memorable: Multimedia presentations can be more engaging and memorable than traditional text-based formats.

6) مزايا استخدام الوسائط المتعددة:

إشراك الحواس المتعددة: يمكن لعروض الوسائط المتعددة أن تشرك المشاهدين من خلال البصر والصوت وربما حتى اللمس أو التفاعل، مما يعزز التعلم والاحتفاظ.
وضوح المعلومات وعرضها: يمكن أن تساعد عناصر الوسائط المتعددة (الصور ومقاطع الفيديو والصوت) في تبسيط المعلومات المعقدة، مما يسهل فهمها وتذكرها.
زيادة تفاعل المستخدم: تتيح الوسائط المتعددة التفاعلية للمستخدمين استكشاف المعلومات بالسرعة التي تناسبهم والتحكم في تدفق العرض التقديمي، مما يعزز التعلم النشط.
مناشدة أنماط التعلم المختلفة: تلبي الوسائط المتعددة أنماط التعلم المختلفة (البصرية والسمعية والحركية) من خلال تقديم المعلومات بطرق متعددة.
أكثر جاذبية وتذكرًا: يمكن أن تكون العروض التقديمية للوسائط المتعددة أكثر جاذبية وتذكرًا من التنسيقات التقليدية القائمة على النصوص.

(7) Data reduction in image analysis:

Data reduction is a crucial aspect in image analysis due to the large amount of data contained in an image. Common techniques include:

  • Downsampling: Reducing the image resolution by discarding pixels.
  • Color quantization: Reducing the number of colors in an image.
  • Feature extraction: Extracting only relevant features (e.g., edges, shapes) from the image for analysis.
  • Compression: Applying compression techniques to reduce file size without significantly impacting the information needed for analysis.

(7) تقليل البيانات في تحليل الصور:

يعد تقليل البيانات جانبًا مهمًا في تحليل الصور نظرًا للكمية الكبيرة من البيانات الموجودة في الصورة. تشمل التقنيات الشائعة ما يلي:

Downsampling: تقليل دقة الصورة عن طريق التخلص من وحدات البكسل.
تكميم اللون: تقليل عدد الألوان في الصورة.
استخراج الميزات: استخراج الميزات ذات الصلة فقط (مثل الحواف والأشكال) من الصورة لتحليلها.
الضغط: تطبيق تقنيات الضغط لتقليل حجم الملف دون التأثير بشكل كبير على المعلومات المطلوبة للتحليل.

(8) Rendering:

Rendering is the process of converting 3D models, scenes, and animations into final images or videos. It involves calculating lighting, shadows, textures, and applying effects to create a realistic

(8) التقديم:

العرض هو عملية تحويل النماذج والمشاهد والرسوم المتحركة ثلاثية الأبعاد إلى صور أو مقاطع فيديو نهائية. يتضمن حساب الإضاءة والظلال والأنسجة وتطبيق التأثيرات لإنشاء صورة واقعية


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