Journal of Machine Vision and Image Processing

JMVIP is the journal of Iranian society of machine vision and image processing published in Persian biquarterly. Due to permission from the ministry of science, research and technology, JMVIP articles are indexed in the Islamic countries’ Science Citation Center (ISC). JMVIP aims to peer review and publish regular articles present major technical researches or survey articles offer reviews of the topics in the field of machine vision and image processing.

1. A general descriptor based-on weighted local binary pattern for infrared images retrieval

Pages 1-12

Mohammad Hossein Shakoor

2. A new descriptor for biometric user authentication systems based on optimized features of finger knuckle print and fingernail

Pages 13-25

Hadis Heidari; Abdolah Chalechale

3. An Efficient Method for Early Glaucoma Screening based on Calculating Optic Cup to Disc Ratio Using Convolutional Neural Networks

Pages 27-43

Fatemeh Maadi; Neda Faraji; Mohammadreza Hassannejad Bibalan

4. Detection of the Location and Angle of Saffron Flowers using Deep Convolutional Networks

Pages 45-55

Mohammad Reza Mohammadi; Mehrdad Karami

5. Unsupervised Feature Learning for Blind Quality Assessment of Super-Resolved Images

Pages 57-67

Maryam Karimi; Mansour Nejati

6. A Computer Vision Algorithm based on Dynamic Neural Fields for Multiple-Object Tracking

Pages 69-81

Shiva Kamkar; Hamid Abrishami Moghaddam; Reza Lashgari

Journal Archive

1. A general descriptor based-on weighted local binary pattern for infrared images retrieval

2. A new descriptor for biometric user authentication systems based on optimized features of finger knuckle print and fingernail

3. An Efficient Method for Early Glaucoma Screening based on Calculating Optic Cup to Disc Ratio Using Convolutional Neural Networks

4. Detection of the Location and Angle of Saffron Flowers using Deep Convolutional Networks

5. Unsupervised Feature Learning for Blind Quality Assessment of Super-Resolved Images

6. A Computer Vision Algorithm based on Dynamic Neural Fields for Multiple-Object Tracking

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