English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present an automatic program of blue whale photo-identification for mobile devices. The proposed technique works in the wavelet domain to reduce the image size and the processing time of the proposed algorithm, and with an edge enhancement filter, the characteristics of the blue whale are preserved. Additionally, an image palette reduction algorithm based on local image complexity estimation is introduced to eliminate redundant colors, thus decreasing the number of pixels that are bad classified in the segmentation process and minimizing the resource consumption of the mobile device. The segmented image is obtained with the FCM (fuzzy C-means) or K-means algorithms incorporating a dynamic filtering which is proposed in this paper to improve the brightness and contrast of the acquired image increasing the performance of the image segmentation. Experimental results show that the proposed approach potentially could provide a real-time solution to photo-id of blue whale images and it can be transportable and portable power for mobile devices. Finally, the proposed methodology is simple, efficient, and feasible for photo-id applications in mobile devices.

Photo-id of blue whale by means of the dorsal fin using clustering algorithms and color local complexity estimation for mobile devices