Digital image collection as rapidly increased along with the development of computer network. Image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the database that matches the user's requirements in similarity evaluations such as image content similarity, edge, and color similarity. Retrieving images based on the content which is color, texture, and shape is called content based image retrieval (CBIR). The content is actually the feature of an image and these features are extracted and used as the basis for a similarity check between images. The algorithms used to calculate the similarity between extracted features. There are two kinds of content based image retrieval which are general image retrieval and application specific image retrieval. For the general image retrieval, the goal of the query is to obtain images with the same object as the query. Such CBIR imitates web search engines for images rather than for text. For application specific, the purpose tries to match a query image to a collection of images of a specific type such as fingerprints image and x-ray. In this paper, the general architecture, various functional components, and techniques of CBIR system are discussed. CBIR techniques discussed in this paper are categorized as CBIR using color, CBIR using texture, and CBIR using shape features. This paper also describe about the comparison study about color features, texture features, shape features, and combined features (hybrid techniques) in terms of several parameters. The parameters are precision, recall and response time.

Pixel value graphical password scheme was introduced with the aim to solve problems faced by users during authentication process that arising from current graphical password scheme weaknesses. Even though the idea of graphical password scheme is still under analysis stage, many researchers have come out with a lot of vulnerabilities finding for current graphical password scheme. Literature studies on vulnerabilities finding has contributed for a development of method design features and requirements for pixel value graphical password scheme. This paper is organized as begin with a brief introduction on graphical password scheme, followed by literature study outcome, discussion on features and requirements, and enclosed with topic conclusion.

Content Based Image Retrieval, CBIR, performed an automated classification task for a queried image. It could relieve a user from the laborious and timeconsuming metadata assigning for an image while working on massive image collection. For an image, user's definition or description is subjective where it could belong to different categories as defined by different users. Human based categorization and computer-based categorization might produce different results due to different categorization criteria that rely on dataset structure and the clustering techniques. This paper is aimed to exhibit an idea for planning the dataset structure and choosing the clustering algorithm for CBIR implementation. There are 5 sections arranged in this paper; CBIR and QBE concepts are introduced in Section 1, related image categorization research is listed in Section 2, the 5 type of image clustering are described in Section 3, comparative analysis in Section 4, and Section 5 conclude this study. Outcome of this paper will be benefiting CBIR developer for various applications.

An image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the large database that matches the user's requirements in similarity evaluations such as image content similarity, edge, and colour similarity. Retrieving images based on the contents which are colour, texture, and shape is called content-based image retrieval (CBIR). This paper discusses and describes about the colour features technique for image retrieval systems. Several colour features technique and algorithms produced by the previous researcher are used to calculate the similarity between extracted features. This paper also describes about the specific technique about the colour basis features and combined features (hybrid techniques) between colour and shape features.

Mangroves forests provide a support to the coastal livelihood, ecosystem, socioeconomic and also the environment. In Malaysia, the mangroves forest has been in declining rate causes by a few factor such as conversion to shrimps ponds, urban development and tourism. Such threats led to increasing demand for detailed mangrove maps for the purpose of measuring the extent of deterioration of the mangrove ecosystem. However, it is difficult to produce a detailed mangrove map mainly because mangrove forest is very difficult to access. Remote sensing technology provides a genuine alternative to the traditional field-based method of mangrove mapping and monitoring. This study analyses and map the mangrove forest changes at Pulau Kukup, Ramsar Site Johor from 2013 until 2021 using the Normalized Difference Vegetation Index (NDVI). The findings of this study are the mangrove forests in Pulau Kukup, Ramsar Site Johor, revealed an unfavourable shift leading to deforestation from 2013 to 2016. However, between 2019 and 2021, the mangrove forest improves as the forest’s vegetation grows.